For a rich country, it’s surprising how the US keeps finding itself wanting for fundamental equipment. It is one thing for a shortage to last for a few days or weeks. When it drags on for years, it points to a fundamental problem. In this case, a problem with energy and specifically the physical infrastructure of the grid. Thanks to electric vehicles and AI data centers, we are asking the grid not just to grow, but to grow faster. The grid’s physical components are well understood with many competitive suppliers. Yet lead times and prices keep increasing, resulting in cost overruns and extreme delays to grid expansion. This situation, with transformers specifically, is a testament to American sclerosis. But the news is not all bad: fixing it is within our power, and innovation is coming to help. A country that can build the world’s most advanced AI models but can’t get an electricity transformer delivered in under two years is not a country with a technology problem. It’s a country where the machinery of abundance has been taken apart, piece by piece, by people who did not build it, some who actively resent it, and were never asked to put it back together.

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Surging Demand for Power, Even Before AI

For the first time in my adult life, demand for energy supplied through the electric grid is going up in the US. Electrification is driving the growth (i.e. shifting demand from fossil fuels to the grid) and now AI data centers. Grid planners assume stable, predictable growth of both supply and demand. It has been anything but.

Notably, the total amount of energy consumed, including electricity, transport, and heating, is mostly stable.

But demand for electricity specifically has started creeping upwards (note the difference in scale of the Y-axis and X-axis). Electricity represented about 16% of primary energy consumption in 2024.

In 2026, this growth is in the news because AI data centers are accelerating demand even more, but demand has been growing since 2018. Starting around 2012, EVs shifted demand from fossil fuels to grid-distributed electricity

The result is intense demand for all components of the grid, including the basic components needed to connect parts of the grid together. The biggest bottleneck for the last few years has been transformers.

As their name suggests, transformers transform voltage, which is at one level in a given circuit, to a different voltage in another. Transformers connect different parts of the grid where different voltages are needed. Each connection requires a specific kind of transformer, so essentially every power cable is connected to either a generator and a transformer, a load and a transformer, or between two transformers. This means that there are a lot of transformers on the grid and there are extreme design limits to what can be done without them.

There are two common kinds of transformers: high-voltage transformers and distribution transformers. Power plants generate immense amounts of power. But to get to the devices that use electricity (known as the load), engineers have to pick the best way to get it there, balancing the cost of the equipment with the efficiency of transmitting and safety of the relevant system. By far, the most efficient way to send energy is via high-voltage transmission lines, operating from 69 kV up to 765 kV in the US. Transmitting power at high-voltage is efficient but super dangerous. The higher the voltage, the more likely electricity will arc to the nearest ground. It would also fry all your electronics, which in the US operate at usually 120 V and some power-intense appliances at 240 V. So high-voltage lines are treated like freeways to move huge amounts of power around. Like a freeway, there must be offramps and smaller streets to get to the destination (in this case, the load). Power leaving the transmission line is like getting off the highway onto a quiet street. Distribution lines attach to the transmission line and run to homes and buildings, operating at medium voltages (2.4 kV to 34.5 kV). The lower voltages are safer around more people and closer to the voltage residential and commercial appliances use, even if more power is lost at lower voltages. Getting it from the distribution network to a home or office requires another step down, from 2.4-34.5 kV to 120 V.

At each connection between different voltages, a transformer is required. Getting the power from the generator to the high-voltage transmission line usually requires a kind of high-voltage transformer called a generator step-up (GSU). Step-down high-voltage transformers are the offramps where power leaves the transmission lines for the distribution lines. Distribution transformers are what hangs on the lines outside your homes, converting the power to the 240V or 120V that home appliances use. Distribution transformers are by far the most common kind of transformer. The quantity of each kind of transformer in the US reflects a similar ratio of freeways to neighborhood streets. In 2024, NREL estimated there are about 10,000 times as many distribution transformers as large power transformers (60-80 million compared to 4,900 to 6,799).

Unfortunately, we do not have enough of any of these. This shortage poses unique risks to maintaining the grid, let alone expanding it to meet new economic demands. Each transformer represents an essential node in the network. If a node is lost and it takes years to replace, that part of the network goes dark. Transformers are lost all the time, from cars crashing into electricity poles to wildfires to intentional sabotage. In a future conflict, they are prime targets for drone attacks, with most networks completely immobile, exposed, mapped, and easily identifiable.

Thankfully, the feds have at least oriented themselves to the problem, even if investing in the grid is mostly a state and municipal issue. National Renewable Energy Lab estimates “distribution transformer capacity may need to increase 160%–260% by 2050 compared to 2021 levels to meet residential, commercial, industrial, and transportation energy demands.”

In 2023, Harris Williams, an investment bank, highlighted six drivers of transformer spending:

1. Aging infrastructure (as noted above by NREL)

2. Grid resiliency (i.e. having multiple connections between generation and load and being able to quickly replenish downed lines due to wildfire, sabotage, etc.)

3. Legislation driving more demand via subsidization

4. Renewable energy generation driving new kinds of supply

5. High-growth end markets (like AI data centers and electric vehicles)

6. Reshoring initiatives to do more domestic manufacturing

More demand without more supply had its textbook effect: the remaining transformers are even more expensive. Prices are up ~4x since the 2000s…

…though utilities should be willing to pay even more, given the deadweight loss to the economy. To recap, there are secular trends driving an increasing need for transformers. The demand is structural and sustained. Yet, six years on, prices and lead times stay high. Classically, price is the best signal to entrepreneurs to invest in more capacity here. Yet as of 2026, no new supply has come online in the US.

So why hasn’t supply responded? The answer is locked inside the transformer itself.

An Unfortunate Series of Moggings

Mechanical engineers such as myself love mechanisms, spinning gears, levers, and moment arms that put people directly in control of the machines. Yet, deep in our heart, we know that moving parts are the source of most trouble. A device that can do its job without moving parts is a universally superior design. No gears, no problems. In the vernacular, solid state devices mog devices with moving parts.

Transformers are fairly simple devices with few moving parts. The actual act of transforming voltage takes advantage of electromagnetic induction between two coils (usually copper or aluminum) attached to a core, a big slab of electrical steel. In operation, no parts move. The only moving part on most transformers is a switch that can be thrown manually or in some cases automatically to disable the transformer. These devices have been perfected with all extraneous parts ablated over decades of iteration.

Yet, transformers have a dirty secret.

Most of the components are pretty common: copper or aluminum, oil if used, and switchgear are all commodity devices. Electrical steel is what is causing the problems. Electrical steel has been produced for over 100 years. Sir Robert Hadfield of England created silicon steel in 1900. In 1934, Norman P. Goss patented a method for producing electrical steel with a grain that strengthened its effect. Today, we call these flavors of electrical steel grain-oriented (GOES) and non-grain-oriented (NOES). GOES is the most common in transformers because of its efficiency, while NOES is more common in motors due to the uniformity of its magnetic field. What makes GOES efficient is its purity, which requires fresh steel.

The fate of fresh steel in the US is best encapsulated in the name “Rust Belt”. What killed fresh steel in the US was economics. In the 1960s, Nucor introduced the electric arc furnace (EAF) mini-mill, which used plentiful recycled scrap steel to outcompete most of the aging, unionized steel producers using blast furnaces to make fresh steel. Yes, Nucor mogged Bethlehem Steel. While economics killed fresh steel, environmentalism ensured it would not come back. Blast furnaces require huge amounts of energy and release about 2.33 tonnes of CO2 for every 1 tonne of steel. Fresh steel would have to come from developing countries with low overhead, cheap energy, and either indifference towards climate change or accepting carbon release to preserve critical industries. You-know-who was front and center: as of 2023, China had 56% of global production. But making GOES is well understood and many other countries preserved their production, including Japan, Russia, Germany, and South Korea. In the US, there is only one producer of GOES: Cleveland-Cliffs in the Butler Works facility in Butler, PA. Butler Works produces about 250,000 tons per year across two facilities. North American consumption is approximately 539,000 tons as of 2022. The US is once again mogged by deindustrialization. But this was just the first of several own goals.

Forcing the Future

Six years of high prices should have drawn new investment. It hasn’t. International players should be filling the void, yet they are also delaying expansion. GOES requires precise metallurgy which is a significant barrier for commodity steel vendors to match their quality or the cost structure. A GOES factory can run into the billions and take over 5 years to build and commission. The customer base is relatively small and highly concentrated among transformer manufacturers, creating significant go-to-market risk. The market is small and the bet is enormous. The payback period for a GOES facility can take 10-20 years to recoup the investment, requiring high confidence demand will remain high and no one will create a substitute during that time. This fear is borne out by other bottlenecks in transformers, where even producers that can get enough GOES cannot find enough skilled labor to wind copper. A transformer is physically mostly GOES and copper plus a decent amount of labor.

Those copper wires are almost entirely wound by hand, resisting automation because customers refuse to standardize their designs. Finally, steel is always subject to trade policy risk, which makes it difficult for non-US manufacturers to be sure they will have continued market access and also makes US producers unsure if they will face cheaper imports over the next two decades. Of course, China wants to own their future and continues investing in their own GOES supply. In the US, every entrepreneur that has looked at this has run away screaming, even more than they usually do when trying to build a steel mill in the US.

In fact, GOES isn’t the only option. In the 1970s, Metglas created an amorphous alloy that is even more efficient. Metglas’ brochure claims that, “Compared to silicon steel core transformers, amorphous core transformers will have 50% lower losses at 20% load and 32% lower losses at 30% load“.

The rest of their brochure highlights the total cost of ownership of such a system, which is a business’ way of telling customers not to overreact to the sticker price. Amorphous metal itself is more expensive and the manufacturing process is subscale. In 2021, Metglas estimated they had sold 4,000,000 transformer cores (estimating the total number of distribution cores in the world is tough, but Gemini puts the US alone at 80,000,000). In 50 years of operation, it had achieved 5% market share.

To recap the situation in 2020, power demand from the grid was going up in the US from about 0% to 2% annually. The pandemic hit, causing the usual supply chain disruptions but the real impact would come in 2021: inflation. Inflation ripped through steel, copper, and specialized labor, sending prices up. The backlog grew. But the world needed more transformers, so prices and lead times grew. Without more GOES and more specialized labor, the supply chain would just have to grind through its backlog.

In February 2023, the Biden Department of Energy saw this supply crunch as an opportunity—to ban GOES. Hanlon’s razor applies here: the DOE didn’t attempt to ban the main BOM component for 95% of transformers on the market out of malice. It ran the only playbook it had: raise efficiency standards. For generations, DOE bureaucrats have only been asked to reduce consumption, not manage a growing power load. The DOE still had to show their latest mandatory efficiency increase had a business case. This exercise is functionally a political tool to see how much cost can be borne by the electorate, determining exactly where the regulatory ratchet of efficiency standards comes to rest. Amorphous metal represented a way to support grid growth due to electrification of the economy with EVs and heat pumps with a domestically produced, more efficient, less CO2-intensive metal. The Biden Administration saw this as a win-win.

That helps to explain why, even though the DOE had many policy tools available, including subsidization, they actually chose new efficiency rules that de facto banned GOES and would only allow amorphous metal cores in distribution transformers. DOE 10 CFR Parts 431 is 448 pages long. Mercifully, it puts its proposed efficiency table at the beginning. That table reads as “no more GOES” with another 400+ pages of why that supply shock impacting 95% of the transformer market won’t be a catastrophe.

One year later, the plan was dead. Remember Cleveland-Cliffs, the only US producer of steel? Their plant is unionized. Foreshadowing the growing rift between union workers and the Biden admin, they went to war with the DOE to protect their plant. By April 2024, the DOE had relented and Secretary of Energy Granholm had to do an apology tour, mogged by the union.

Yet the damage was done. No one has built additional amorphous facilities, and no additional GOES suppliers have come online in the US. It’s easy to see why there has been no investment in either commodity: plants often count on 15 year lifespans to generate any significant return. Even with increased demand over time, you have to compete with a globalized product in a market where one political party just tried to ban one of the two options. Will they try again soon? Will the other party try to ban the other option? In that environment, there is no safe investment, so no one makes any. Somewhere in its 448 page tome, DOE bureaucrats insist a GOES factory has options to pivot into other markets; the market’s silence says otherwise.

Bad Energy

The cumulative damage shows up in lead times.

Every month on that table is a month where a hospital can’t add backup power, a school district can’t connect rooftop solar, and a new housing development sits dark. The shortage isn’t an abstraction — it’s a tax on every project that would make daily life better.

By 2024, the market was starting to work through its backlog. Prices were high, but lead times started to return to normal. In principle, all the government had to do was nothing and the market might have corrected.

Reader, the government chose against doing nothing.

To incentivize domestic production, the government did tariffs. Steel, especially foreign steel, especially Chinese steel, was the first to get hit. GOES is subject to a 25% tariff when imported in raw roll form. Copper itself has a 50% tariff thanks to Section 232. But in global whack-a-mole supply chains, most suppliers dodged the tariff because laminations and cores are not tariffed, creating a perverse incentive to move more processing offshore.The tariff punished the raw material and rewarded the runaround. (More recent tariffs have threatened to patch this, and match the 50% tariff on copper.) Meanwhile, Cleveland-Cliffs celebrated the tariffs and promptly charged more for the same mid-grade GOES.

In 2025, the energy research organization Wood Mackenzie estimated the US distribution transformer still had a 10% supply deficit of distribution transformers and a 30% supply deficit for large power transformers. US power prices continue to climb.

Free Electrons

The Kardashev scale models civilizations based on their energy consumption because it is literally a measure of how much can physically be done. In the age of AI, it has become a measure of how much mentally can be accomplished too. The stakes are high, and the pressure reveals what you really believe. (Why else would someone ban supply in a crisis?) It compels institutions to be the most extreme versions of themselves, endorsing galaxy-brain attempts to spur domestic production that stops it dead in its tracks. Worse, no one seems to have acted like it was a crisis. Even worse than that, there is no feedback mechanism besides general discontent with affordability. Today, headlines blame datacenters for high energy prices. Yet there are decades of hairbrained schemes that haunt the supply chain with the realized costs and opportunity costs of their mistakes. In his book Breakneck, author Dan Wang labels the US a society of lawyers and China a society of engineers. Situations like transformers are a case in point.

Increasing use of energy per capita is the best way to improve and enrich humanity, and increasing electrification is the best way to do it efficiently and taking advantage of renewable energy sources. These demands will continue to grow, even though they radically outstrip current supply. Fortunately, innovation and policy options are both available.

There will be progress in the form of innovation. First, Hertha Metals is attempting to make fresh steel here in the US with an innovative new process that is cheaper, less energy intensive, and less carbon intensive. I wish them all the success in the world. Second, solid state transformers (SSTs) are poised to revolutionize distribution transformers. Considering transformers already have essentially no moving parts, solid state transformers have a rather silly name, but the benefits are real (see Drew Baglino’s writing on SSTs). They are more efficient, smaller, and give greater control. The control piece makes for better overall power quality and enables bi-directional power transfer. Traditional distribution transformers are optimized for sending power from transmission to load, but with bi-directional power transfer, homes, vehicles, and batteries on the distribution network can pump power back into the grid when needed (see Justin Lopas’ exciting new startup, Base Power, built around this idea). These innovations will help expand the solutions, but the US is wasting the solutions it has.

Policy problems require policy solutions. Standardizing distribution transformer designs on principles allowing for easy automated manufacturing would instantly unlock more supply. Asking DOE bureaucrats not to commit industrial suicide is trickier. Reforming the Department of Energy would probably require fewer mandates instead of more: maintaining efficiency standards is tacked on to their core responsibility of maintaining the nuclear weapons arsenal. Give somebody else a mandate to grow the grid, hold high efficiency standards, and keep prices low. We expect the Federal Reserve to use monetary policy to achieve maximum employment and stable prices, surely we can do this for the grid. Moreso it is a chance to reset the culture and build a culture of progress. And of course, tariffs haven’t changed anyone’s calculus on domestic production of GOES or transformer assembly. It is too simple to make elsewhere and too complicated to make in the US. Stories like this are endemic to the US industrial base.

I wish it was not so familiar: the professional building class waits for things to get bad enough before some sicko runs towards the problem instead of easier money. Trust in the institutions that manage the infrastructure powering daily life erodes. The steel mills that produce GOES do enough to survive, afraid they will lose their home market let alone attempt to compete globally. The regulators make the perfect the enemy of the good, freezing investment when we need it most. Trade policy manages to push prices up and encourage foreign sourcing but not domestic investment. Together, it represents a long slouch towards cyberpunk, a future state defined as high-tech, low-life. It starts with mismanagement of state resources only addressed through private innovation. Private innovation is the only escape from a web of incompetence and perverse incentives, slowly becoming necessary to sustain civilization as trust in institutions erodes. While I celebrate innovators and am grateful the situation can improve, this scenario is not a triumph of the private sector over the public. The trouble with transformers is a story of wasted time, energy, and treasure to serve select interests at the public’s expense.

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Thanks to Sam Enright, Elizabeth Van Nostrand, Andrew Miller, and my wife, whose beauty and intelligence is unmatched, for reviewing drafts of this post. Any mistakes are my own.

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Making Space Lasers Boring

Every B2B company reaches the same inflection point: enterprise customers demand SSO, directory sync, audit logs, and granular access controls. WorkOS removes that friction, enabling companies to become enterprise-ready without diverting months of engineering effort from their core product…

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4 months ago · Rob L'Heureux and Arena Magazine

For those that need a little more, this article is a profile of Overview Energy. Overview is a startup based on the fancy idea that it is now economical to collect sunlight in space and use lasers to beam it to Earth.

Max at Arena asked if I had any thoughts on contributing to Issue 007 with a James Bond space opera theme, and I knew it had to be space lasers. Growing up, Bond movie marathons were the background noise for most of my Thanksgivings. Goldeneye 64 was one of the seminal games that my brothers and I could play together (I crushed, but we all grew to hate my younger brother’s tactics with proximity mines). Space lasers are one of those topics that existed at the periphery of Bond’s plausibility. Real tech, for sure, but it’s easy to mistake reality for Star Wars.

I wanted to spend time on the messy reality, and it was a good excuse to spend the time with my friend. Marc is a brilliant pioneer in his field, who now has the chance to do something special. The piece is less an stress-test of his economics and more an examination of what must I believe to be true for this thesis to make sense?

Ultimately, the article is a labor of love. My wife was super pregnant when Max asked for ideas (our first baby is now here), and we had been intentionally reducing our commitments. This article was my reach goal, because it has the kind of people I want to see succeed, the kind of tech I want to exist, the kind of writing I like the most (see if you can spot the Tom Wolfe and inspirations), and the kind of magazine I want to support.

Now go enjoy some space lasers.

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Hello. It’s been a minute. While this substack has been dormant, I have written a few things elsewhere.

Arena Mag: Choose Your Adventure on defense procurement reform.
Pirate Wires: Shower/Acc on why the future should be comfortable. (I lost contain on that one.)

For any new subscribers, welcome to the adventure. Here’s another one, slightly too long for email. For the best experience, click through to the web.

The most interesting story in the world right now is China’s economy eating itself. Consumer prices have fallen by 0.1% in the first 6 months of 2025 and industrial prices have fallen by 2.8%. Partially, Trump’s tariffs and reprieves are whiplashing demand and causing a glut of supply, leading to price wars. Enter involution (or 內卷 according to journalist Angelica Oung’s informative post).

Because for some insane reason the Chinese companies don’t focus on “maximizing returns to shareholders” but “minimizing profits so you can kill your competitors.”

They call it being 內卷 or “involuted” although I’ve never understood the meaning of that term either in English or Chinese. I just know what it is.

Imagine a German Mittelstand SME cornered the market in making some obscure but essential widget for more than a century and got the bright idea of outsourcing the manufacturing to China.

For 8-15 years everything works beautiful. Costs plummet and even junior Chinese executives get to fly business class because everyone is so flush. Then, on a cursed day, some Chinese guy figures out how to do it without the Germans.

The $8,000 widget becomes $950 overnight. If you asked him how he arrived at that insane pricing he’ll say “I take my cost. I add my 20% profit. Boom.” But wait! You and the woebegone German are the only ppl on the planet with this technology?

Why not price it at $6000? You’ll make more money because you still significantly undercut the German. You’ll both survive and have more money in your pockets! It’s a duopoly.

Nope! That maniac, even after he buried that Mittelstand that has been passed through multiple generations minting fat profits, will keep cutting costs. Junior executives aren’t flying business no more.

And then he’ll lower prices. On himself.

It’s pathological. I’ve heard Chinese economists beg businesses not to do it. It’s why the stock market in Shanghai sucks. And it’s why the Chinese businesses are beasts.

Involution is not a technical term but a vibe: deliver the same product for less than the other guy. Repeat until one competitor is dead. Angelica’s original post captured how this works for classic industrial products. of Fabricated Knowledge wrote about the same vibe in the semiconductor industry, as Huawei’s ascent in chip design and fabrication powers China’s AI aspirations. Generally, the rule holds: if a Chinese manufacturer can match your performance, it will try to win on price.

Involution, the vibe, is the result of unique Chinese circumstances. In a Western society, involution is a great way to kill a company, comparable to Welchification. But it is China’s national policies that have made it pervasive and expected.

If, like me, you are not immersed in Chinese culture and history, it can be difficult to really understand how a country decided this was a good idea and why otherwise rational actors choose a race to the bottom. Liu He, a visiting scholar at the Hoover Institution stated that, “The perennial deadlock of China knowledge: those who know cannot speak, and those who speak cannot know.” Given China’s secrecy, the picture will always be incomplete, so the best I can do is compile information and cross-reference different sources.

Thankfully, we are in something of a golden age of Western-accessible information about modern Chinese culture, industry, and politics. For those with my insatiable curiosity, I would heartily recommend the linked podcasts and articles:

1. Dwarkesh Podcast: Xi Jinping’s paranoid approach to AGI, debt crisis, & Politburo politics — Victor Shih
   Victor Shih is an expert on the Chinese political system, as well as their banking and fiscal policies, and he has amassed more biographical data on the Chinese elite than anyone else in the world. He teaches at UC San Diego, where he also directs the 21st Century China Center.

2. Dwarkesh Podcast: “China is digging out of a crisis. And America’s luck is wearing thin." — Ken Rogoff
   Ken Rogoff is a former chief economist of the International Monetary Fund (IMF) and author of Our Dollar, Your Problem: An Insider's View of Seven Turbulent Decades of Global Finance, and the Road Ahead.

3. Noahpinion | China's industrial policy has an unprofitability problem
   Noah Smith is an economist and blogger.

4. Yuxi on the Wired | Structure and Interpretation of the Chinese Economy

   Yuxi Liu is a PhD student in Computer Science at UC Berkeley. Generally, I treat Yuxi’s comments as a smart person more fluent in Chinese culture than myself, who has also attempted to synthesize some of these topics. Generally, I am including Yuxi because other sources including Victor Shih and Ken Rogoff highlight similar topics and sentiments that corroborate Yuxi’s summaries.

5. This particular thread by Michael Pettis, Sr. Fellow of the Carnegie Endowment

6. Anything ChinaTalk.

This post is an attempt to synthesize:

• The cultural origins of involution

• How the policy choices to avoid Japan’s economic stagnation produced involution

• The logic of China’s economy that incentivized involution

• How China’s industrial economy is eating itself

• How long China’s economy can eat itself

• Can China stop involution? Will they?

• How Western competitors can survive involution

The Cultural Origins of Involution

Notably, the story that Angelica is telling is cultural. I do not profess a deep understanding of any eastern culture, so I offer this part as my own interpretation of the origins of this culture. Every culture seems to have its own folk wisdom for expecting and preparing for hardship, from famine, war, pestilence, you name it. This received wisdom can become a virtue, through principles like self-discipline and sometimes even in religion.

Eastern religions and cultures have significant strains of asceticism, that practice both self-discipline and self-denial. My understanding is that Chinese society is influenced largely by Confucianism, Daoism, and Buddhism to different degrees but mostly in that order, and all have strains of asceticism. Confucianism is the most permissive for restrained desires but engagement in society and self-mastery. Buddhism calls for an entire renunciation of desires and worldly-life, and Daosim calls for withdrawal from society and natural simplicity. For Western comparisons, I think of Confucianism as approximate to Stoicism that calls for the endurance of suffering and ethical clarity; whereas Buddhism and Daoism are closer to monasteries and vows of poverty. Involution, then, is these principles applied to business. Costs and price are things that a business can master, expecting to “win” simply by surviving through enduring more pain than competitors. For a people who survived a famine in recent history, it is not difficult to imagine the Chinese people cultivating an ethos that prioritizes survival in the face of immense hardship.

Of course, these attitudes predate their current predicament and yet their economy still grew immensely over the prior decades. Culture changes very slowly, so one would expect these principles to endure into the future as well. This moment is unique, though, because the government incentivized these attitudes, seemingly as an accident, as they attempted to avoid Japan’s own limits to growth.

Don’t Be Japan

In the 1980s, Japan was the future. Its GDP grew at 3.89% annually, ahead of the US’ own 3.07% during the same period. American college students were encouraged to learn Japanese and work in Japan (Happy Future favorite Patrick McKenzie aka patio11 has referenced these attitudes coloring his own decision to go to Japan straight from college). In the 1990s, this growth came to a screeching halt. From 1991 through 2003, Japan’s economy would only grow at 1%, far below the growth rate for other industrialized countries. This period would become known as the “Lost Decade” and a cautionary tale for other Eastern economies looking to integrate with Western economies.

China carefully studied Japan’s failures to develop their own strategy, per Ken Rogoff, former Chief Economist of the IMF, who offered first-hand accounts of Chinese officials telling him they did not want to end up like Japan. One modification the CCP required to the Japanese formula is that the people doing the work and getting rich do not attain political power. Political power following economic empowerment was a core feature of US-enabled development efforts in Japan and its former colonies of Taiwan, South Korea, and Singapore. Note that the US was not always the one pushing for democracy in those countries, but the US often set the terms for market access and provided powerful incentives to create legitimate governments.

Beyond political power, there were other lessons from Japan’s experience. Taiwan, Japan, and South Korea all followed this path and hit a ceiling of one kind or another. Taiwan essentially maxed out their GDP available for an island, as TSMC became so important it dominated the GDP of the country. South Korea has diversified more successfully and increasingly resembles Western countries, economically and culturally. The CCP would love to fully use every inch of land and to have leading-edge foundries the way Taiwan does, and South Korea’s diverse, industrial economy is desirable if not its inclination towards Western consumerism. Japan’s Lost Decade, though, held a lesson about how the US can sabotage their growth with political pressure.

Ken Rogoff makes the case in Our Dollar, Your Problem that Japan’s troubles fundamentally came from US policy. Through the 1980s, Japan had deliberately controlled its currency relative to the dollar to support an export economy to the US. The export economy was important because it forced local companies to compete worldwide, and only the winners of the global markets would be awarded state support. This strategy worked extremely well, with many Japanese manufacturers outcompeting American manufacturers like Toyota in cars or Intel being forced to focus on CPUs instead of memory due to Japanese competition. Notably, during this time the Japanese pursued their own form of involution. Japanese competitors were known for their obsession with quality and efficiency, but not creating new categories of products. They would relentlessly innovate on the process of manufacturing and deliver low-cost, high-quality products while fighting each other for market share. Profits would come later, what mattered was getting to scale to win international prestige, domestic support for more financing, and to drive out international competition.

These tensions forced US politicians to pick a side: do you want local manufacturing? Or do you want cheap imports from other countries? US politicians largely decided they wanted cheap imports, but enough were sick of Japanese dominance they forced Japan to appreciate their currency. In 1985, Japan and the US would sign the Plaza Accords, which allowed for their currency to make their exchange rate more free. That is the trigger that Rogoff cites for the root of Japan’s lost decade, the 1990s, though other factors like other competitors mirroring their strategy were contributing problems. The crisis would not hit until 1992, though, seven years later.

Yuxi offers a summary of how China perceived Japan’s crisis:

To prepare the ground, several money faucets turned on:

• The lowered interest rate made it cheap to borrow money from banks.

• The Japanese households continued to save over 50% of assets in bank saving accounts.

• The Foreign Exchange Law was reformed in 1980, allowing freer cross-border capital flow.

• Wages remained low in general, as corporations persuaded labor unions to keep wage demands low on the grounds of maintaining international competitiveness. This allowed corporations to keep more money for investment.

• The Japanese state issued less bonds to decrease [the] deficit, leaving more money out of government hands.

The net result was a large amount of money that could flow quickly here and there. Such liquidity is not a bubble in itself, but enables bubbles to form and blow up quickly.

…bank loans were not based on a careful credit rating based on predicted future cash flow, but backed by land.

When this bubble burst in 1991, Japan was stuck. The land alone could not justify the asset’s valuations. Everything would have to be marked down to some new, lower price. The whole economy would slowly mark itself down, slowing investment to a crawl. That process is why the Lost Decade took the course of a decade, rather than one bad year.

In short, there was a lot of good money chasing bad. While the projects may provide some return, they were often below the cost of financing those projects, meaning value was being destroyed. Yuxi and Rogoff both share stories of how aware of this failure mode is among Chinese citizens and party members and how resolute they are in avoiding it.

To summarize, Japan had falsely believed:

• Western integration would always be to their benefit. Their GDP growth was linked, and trusting Western economists meant their economies would always grow together.

• Experimenting with monetary policy is low risk, as decisions can be unwound quickly.

• Credit ratings do not matter.

The lessons the CCP drew include:

• Liberalize trade at your own risk. The US is defending its interests, and liberalizing too fast, if at all, can threaten the whole project.

• Financial crises are to be avoided. A country may never fully recover the lost growth from a financial crisis.

But the core lesson was ignored. Investing below the cost-of-capital is value destructive, but for the CCP, the purpose of investing is not to create profits. It is to preserve control.

The Logic of China’s Economy

Preserving the power of the Chinese Communist Party (CCP) is the ultimate goal of China’s economic strategy. In the Dwarkesh Patel podcast linked above, Victor Shih states plainly:

“But what time and again leads to suboptimal policy is the Party’s instinct to preserve itself, and in a way worse than that, to preserve its power. It’s not just ‘Let’s do this thing because it will lead to a better public health outcome and we’ll survive politically.’ They’re mindset is, ‘Even if we would survive politically, if doing that would result in a loss of power—like having less control over the banks or scientists becoming more independent—then they would say, ‘Let’s not do that.’”

Modernization and profits are subservient to this goal. If modernization and profits deliver greater control, the CCP supports it. If they reduce CCP control, the CCP is against it. After Mao’s devastating Cultural Revolution, the CCP realized their model for planning an economy was jeopardizing their hold on power, as starvation racked the country. They had to embrace some modernization and market-based approaches to maintain legitimacy and control. After Mao’s death, there was a chaotic political struggle that Deng Xiaoping won. After a tour of Japan, he basically decided the best path to wealth is making stuff for Americans and participating in their markets, which required pivoting away from the USSR. Deng and his disciples would continue to watch Japan’s Lost Decade and attempt to steer around.

Yuxi summarizes the logic of this new economic strategy:

1. The party controls the state. The party controls the military. The party controls the legislature. There must be no separation of powers.

2. The state knows better, because the state aspires to plan over decades, unlike people or companies.

3. China deserves to be a center of civilization. Not necessarily better than everyone else, but must be one of the best.

4. Never forget national humiliation. (勿忘国耻) The international world is a world of anarchy, and might makes right. Backwards countries are beaten. (落后就要挨打)

5. Power comes from technological development. Development is the only hard truth. (发展才是硬道理)

6. To be one of the best, China must catch up to the Western countries.

7. To catch up, it must develop its economy. The economy depends on scalable industries of material products (实体经济), such as steel and silicon.

8. People do not know how they should spend their money. Their money must be extracted to be rolled into investment for the future. The far future is what matters, not the present, and not even the near future. If people are left with too much money, they will waste it.

Combined with the population structure, these principles explain much of the recent Chinese economy.

I would highlight a few other key dimensions, related specifically to manufacturing-based economy:

9. The quality of exports must be high. American consumers don’t have to choose Chinese goods. While there is a market for low-cost, low-quality goods, there is a much bigger market for low-cost, high-quality goods (with cost relative to what it would take other countries to make them).

10. Local supply and demand is key to self-sufficiency, which is key to self-determination for the party. As the Chinese market develops, it will drive demand for local consumption of locally manufactured goods.

11. Even if local demand dominates local supply, exports are important. Exports enable scale, create advantageous relationships with other countries, and deny global competitors from getting traction while creating jobs at home. Those jobs are important for people to have a stake in the system and to create money to be extracted for future investment.

Reflect on Yuxi’s point #8:

People do not know how they should spend their money. Their money must be extracted to be rolled into investment for the future. The far future is what matters, not the present, and not even the near future. If people are left with too much money, they will waste it.

This concept is foundational to a communist political party that barely tolerates personal property. Yuxi highlights that the Chinese stock market did grow 2x, but at a time when their GDP grew 20x. For comparison, the S&P500 grew 4x in that timeframe while US GDP grew 3.5x.

The biggest unwritten tax in China is that the party controls investments. The party determines what anyone can invest in and how much they can make. Their stock market is controlled both directly with controls on prices and indirectly by placing party members in the business unit that can directly choose where to invest. If equity is a bad investment, the only place left to go are the banks, which are nationalized and answer directly to the party. Favored investments get loans, unfavored ones do not. Savings rates are ~2%. Government bonds are 3.5-4%.

Victor Shih explains:

“You can’t go into a bank and say, “Look, I make robotics. This robot I’m going to make is going to be highly profitable down the road, but I can only make ten of them.” The bank would be like, “This is BS." I know a lot of startups don’t make any money, but at some point, notionally, you have to start making money.

Whereas the socialist banking system basically says, “Even if you never make any money, or hardly any money, that’s okay. As long as the Chinese government tells us this is a strategic sector, and as long as you can prove to us that you can actually produce the thing we want you to produce, if you never, ever make money doing it, that’s perfectly fine.” (Emphasis mine.)

To summarize, an industrious Chinese citizen’s options are:

1. Work for the state in government

2. Work for the state in a state-owned enterprise

3. Work for the state in a company

4. Work for the state in a favored area for R&D

5. Gamble Invest in real estate

Guess which one of these became a huge asset bubble? In 2021, China’s real estate bubble burst, which is adding stress to the CCP’s strategy. Chinese real estate had made the same kind of mistake as Japan: they put too much good money after bad. The value of the land was not worth the debt paid for it, and the bubble burst when the government could not stomach loaning to the sector any more, as evidenced by Evergrande Group’s default in 2021. That effectively closed the door on the one asset class the average Chinese citizen could use to build wealth. Since 2021, Chinese workers are extremely dependent on jobs to build any kind of wealth and social mobility.

Victor Shih summarizes this as a philosophical difference between socialism and capitalism:

“For socialism, they only care about output. It’s like, “Okay, whatever capacity we’re thinking about—whether it’s grain production or metal production or, these days, robotics—we just want more of it.” So then the state can use the state banking system, which they control, to allocate huge amounts of capital to maximize the output of all these different things they care about. But when you maximize output, you don’t necessarily make money doing that.

Whereas capitalism wants to maximize profit, which is the difference between the cost of production and the amount you can earn from selling the output. For socialism, they don’t care about that.”

How China’s industrial economy is eating itself

The first six months of 2025 has seen tremors across the Chinese economy, and the torrent of news and analysis drove my interest in the subject (and why this post has taken so long to come together).

Through May and June, as US tariffs roiled the markets, Chinese prices started deflating, presumably because there was a glut of supply and China had to cut prices even more to keep factories at full utilization (and maximize employment).

CN Wire in May:

JUST IN: China May

Annual CPI -0.1% [Est. -0.2% Prev. -0.1%]
Monthly CPI -0.2% [Est. -0.2% Prev. +0.1%]
Annual PPI -3.3% [Est. -3.2% Prev. -2.7%]
Monthly PPI -0.4% [Prev. -0.4%]
Food price -0.4% y/y, -0.2% m/m.

Industrial profits in particular nosedived:

China's industrial profits fall further in June

BEIJING (Reuters) -China's industrial profits continued to fall in June, data showed on Sunday, as entrenched producer deflation put more margin pressure on businesses in the face of subdued domestic demand and lingering global trade uncertainty… Profits at China's industrial firms fell 4.3% in June from a year earlier, following a decline of 9.1% in May, while first-half profits were down 1.8% versus a slide of 1.1% in the period from January to May, National Bureau of Statistics data showed.

The trend continued in July, signaling their industrial markets were contracting.

The subsidies and incentives of the party dramatically shape the choices of manufacturers. Again, the profits of the business do not matter to their investors i.e. the party. The main thing the party cares about is that they are moving products in a favored market and the subsidies will follow. The secondary thing their investors care about is that they are providing jobs, which keep the public bought into the system that enables them to direct funding.

Today, favored markets are essentially at Xi Jinping’s discretion, and he likes industrial equipment and self-sufficiency. Noah Smith makes the case that China is not really an export-driven economy. 80% of what they produce is for internal use. It’s the remaining 20% that gets sold to the rest of the world. After all, that 80% covers one billion people, so a surplus 20% would cover roughly 250 million people.

Participating in favored markets is just the first step towards getting government funding. After the first Chinese attempt to break into semiconductors with Made in China 2025 turned into a debacle, Xi recalibrated his expectations for how subsidies should be awarded. The policy shifted to something like “pay for performance”. Connections and trust matter, but the party would reward volume. Build things that people want, and the winners will get more money. Wary of subsidizing goods consumers didn’t want, the CCP decided they needed a better product and invited Tesla to participate in China. That allowed Chinese competitors to reverse-engineer Tesla’s success then scale with government subsidies. These new Chinese EV companies could outcompete Tesla with equivalent products at lower prices, thanks to great engineering, free financing, and insensitivity to profits. There are now news articles like China’s EV price war is heating up. What’s behind the big discounts? with facts like, “The average car price has fallen by around 19% over the past two years in China to around 165,000 yuan ($22,900).”

Similarly, after the collapse of the one asset class the average Chinese person could buy to build wealth, the average Chinese citizen is extremely dependent on their job. The party knows this and is paying factories to keep producing units, at least if people are buying. So now the party rewards both overproducing units and selling units, while being indifferent to price. So the answer is to slash costs anywhere they can, keep producing units, keep people employed, and wait for the government to reward this behavior with subsidies.

The result is deflation with consumer and industrial prices falling. Because there are no profits, the only way to keep a company alive or build wealth is to seek government financing, so entrepreneurs’ decisions are constrained in which markets they will compete in, how much they must keep investing in R&D to compete against their peers, and how low they must cut their prices to move units to keep factories full.

How Long Can Involution Last?

The short answer: a very long time. A company would simply go bankrupt if they invest below their cost of capital. The analysis is pretty simple: how much do they have and how much are they losing every year will tell you how long they can last. They can take on other financing options to extend their runway, typically equity or debt, but even if someone believes the company can change, if they do not, it is still a straight line to bankruptcy. A country is not much different, but its financing sources are more diverse by virtue of having all the guns.

Like most governments, the state of China is funded by the people of China. What I had not fully appreciated is exactly how much they give up to the government. The US thinks in terms of the tax rate, the amount the government takes from any given transaction or source of income/capital. Even California dreams of the level of control of the CCP (sometimes, I wonder, how literally).

A breakdown of tax receipts from China starts with domestic value-added taxes (VAT), corporate income taxes, land and real-estate taxes, import VAT, and consumption taxes. Additionally, they have non-tax revenue from administrative fees, remittances from state-owned enterprises (SOEs), and royalties from natural resource exploitation. Altogether, in 2024, they had ¥174.9 trillion which is roughly USD$1 trillion. In 2024, the IRS collected about $5 trillion in income taxes in the US. Both are running a deficit, with China expecting to spend ¥219 trillion ($1.5 trillion—same source) compared with the US spending $7 trillion. Compare that with China’s 2024 GDP of ~$18.4 trillion and the US GDP of $29 trillion for something like an all-in tax rate of 5% for China and 17% for the US. If taxation is theft, China is the lesser thief.

To bring this back to manufacturing, China has essentially the wealth of the entire country to direct to whatever the party wants, and the party wants to stay in control. While they have effectively $18.4 trillion to direct at self-sufficient industries and own future tech, they do have to balance this against ensuring social stability. CSIS estimates China has put $230B of subsidies towards their electric vehicle program from 2009-2023. The Congressional Research Service estimated the Made In China program, including the EV program, was roughly $426B of subsidy. How much of that debt is going towards productive assets is anyone’s guess, but no one believes it is 100% good. See Michael Pettis’ thread for more discussion of the extent of bad debt.

A naive analysis is that $426B of subsidy out of $18.4T GDP would last for 40-80 years of investment. That is just one year’s worth of GDP even if they never made another yuan off their investments, but the reality is much worse:

• China has to finance every industry

• China does make some money off it even if they do not fully recoup their costs

• China could confiscate the society’s existing wealth that is not captured in GDP,

• China would have to live with the social unrest as their society slowly decays and starves as the government dominates GDP e.g. North Korea.

These are not impossible events. Similar things happened in China under Mao not in the 1960s, though it is hard to believe anyone in the CCP wants to go back there. However, the CCP has realized the national policy is backfiring and already moving to change things.

Can China Stop Involution? Will They?

Per Bloomberg:

“In July 2025, China’s Politburo vowed to stop what they call “irrational price competition”. President Xi himself called for an end to involution… As China tightens priorities for the next five years in the upcoming October plenum, Xi faces a challenge how to coax CEOs to cut production, consumers to accept higher prices, and local officials not to compete for new investments crowding into the same sectors. Analysts say any supply side reforms will likely be gradual to avoid job losses and painful repercussions for the economy.” (Emphasis mine.)

China’s industrialists are also sounding the alarm. Zeng Yuqun, the founder of battery-manufacturer CATL, highlighted involution as a significant problem in a rare interview in late July 2025 (updated with a translation by Yuxi):

Q: 你现在有企业家普遍的危机感吗？

有，主要来自“卷”。不做研发只卷价格的风气很坏。但也不是没办法。要用新的商业模式去破它。比如换电，大家都卷电池的价格，一搞换电，电池是租的，价格就卷不成了。

Q: Do you feel the same sense of crisis among most entrepreneurs now?

Yes, mainly from "involution". The atmosphere of not doing R&D and only involuting on prices is very degenerate. But it's not like there's no way out. We need to use new business models to break it. For example, change to battery swapping. Everyone is involuting on the price of the battery, but if we begin using battery swapping, the battery is rented, and the involution on battery price is moot.

The primary plan the government has at the moment is restricting loans and consolidation: declare the most competitive companies the winner and direct subsidies to them. For political reasons, these companies may be directed to buy competitors or create jobs in the most politically sensitive provinces. As Michael Pettis noted, the loans are still out there. The CCP can let some companies go bankrupt, it can let the provinces share in some of the pain, but it is constrained by the need for maintaining social order with both jobs and preserving the people’s wealth. Chinese bankruptcy should also not be confused with American bankruptcy, where the company folds but any wealth extracted by executives is theirs to keep. Instead, the CCP will demand money back from investors and founders.

Capitalists tend to assume at that point, with consolidated industrial giants, these companies would be effective monopolies and would then raise prices. I am skeptical that it is realistic.

For one, the government already coordinates action among key industrial giants. For example, Beijing effectively forced the only US producer of rare earth elements, Mountain Pass, out of business in 2015 by cutting prices by 80% before letting prices go back up.

Two, Chinese citizens are struggling to pay their bills and living in a subsidized society, including even things like food delivery. Raising prices in this environment would be painful and would hurt even more if it costs wages.

Three, higher prices hurt exports even more. Tariffs are effectively already driving up the price of Chinese goods, so raising prices more would only hurt sales more overseas. There is not perfect elasticity here, and China has access to markets without significant tariffs, though they are often in developing economies with the least resources to shoulder higher prices.

Bloomberg’s analysts expect China to be able to solve this situation, albeit slowly and painfully over years, not months. I am inclined to agree. Given the logic of the Chinese economy and their multitude of goals, it seems more likely the CCP would prefer a long drag on economic prosperity borne by Chinese citizens rather than a shorter period of immense pain that would risk their power.

Good luck to you, Spartan.

Western industrialists are not without options in the face of ruthless competition. Yes, there is abundant evidence they are selling below cost in some markets, but even that is cope. Chinese engineers are innovative, highly skilled, and industrious. They achieve things that they set their mind to. The key is that the government will only pay for them to achieve certain things.

Here, it is critical to distinguish between products and commodities. A product is inherently differentiated. It can do something uniquely and has some unique value proposition associated with it. A commodity is intentionally not differentiated but standardized. Rather, it is fungible: copper is copper, electrons are electrons.

Product entrepreneurs have to ask themselves: what can’t, or won’t China do? The main thing they cannot do right now is raise prices, which is the real test of a business. Take it from Warren Buffet:

"The single-most important decision in evaluating a business is pricing power. If you've got the power to raise prices without losing business to a competitor, you've got a very good business. And if you have to have a prayer session before raising the price by a tenth of a cent, then you've got a terrible business. I've been in both, and I know the difference."

To establish pricing power, one has to innovate around the Chinese ecosystem, likely taking risks about where and how to integrate into it. Adding services, guarantees, and complements outside the core of what Chinese firms can offer is critical, as they often give customers certainty for which they are willing to pay. Products relating to economic and national security are mostly isolated from Chinese competition, due to what remains of Western common sense. However, it is imperative that they compete to the same quality level and scale as Chinese competitors to produce a credible deterrent.

Commodity products are a different story. , co-founder and COO at Base Power and formerly Head of Manufacturing at Anduril and a Lead Engineer on Starship Manufacturing at SpaceX, wrote an exceptional post about why Tariffs are an Admission of Defeat, a perspective I share. Still, I worry that this is insufficient to address key bottlenecks in our supply chain. Since Trump launched his tariffs, China has consistently retaliated with its control of rare earth elements. Tariffs are a blunt instrument to establish a floor for importers under which Western companies operate. That price floor might have saved Mountain Pass, but it is not as good as having guaranteed demand. Their mine in the Mojave has since been sold and reformed as MP Materials. What would secure MP Material’s future is long-term supply agreements at fixed prices. The price between what they pay to MP Materials and the market (Chinese) rate is the insurance against Chinese coercion. US industrial policy would do well to incentive those agreements too and foster market competition for them to kickstart a moribund domestic supply chain for commodities we will need.

Ultimately, Western companies must focus on surviving the Chinese manufacturing juggernaut and innovating around it. Involution will not last forever. The CCP does not want their economy to operate this way, it is not intentional, and it is acting to stop it. Their total control of the economy means it will be some other way, though it is still subject to their perceptions of what is in the national interest, which is likely to remain focused on self-sufficiency and strategic competition with the US. China will remain a massive market with a deep pool of talented, hard-working, ingenious people, all bound for the time being to the command of Xi Jinping for as long as he has the strength to stay on top.

The core lessons from their age of involution are the limits of centralized planning, the perils of authorities believing they can make investment decisions better than markets, and the pain inflicted on common people by one party rule. A recurring question in my mind from learning modern Chinese history is, “If the CCP would do this to their own people, what would they do to us?” China will be a force in industry for generations but allowing it to be the only force is no longer an option.

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DC was only sieged once, by enemies. In the War of 1812, the British retaliated against American incursions into Canada by invading and burning Washington, DC. The city would burn for 26 hours before a storm put out the flames. (Mental note: Burning a city in a swamp is maybe not the best siege tactic.) DC got better, though in my own experience it fundamentally grew in wealth and cosmopolitan aspirations after 9/11. It seemed every year I came home from college or from my job on the West Coast, new buildings went up, the restaurants and bars got better, and prices for everything went way up. All that seems to have come to an end.

From the moment the second Trump administration (T2) took office in January 2025, they went about downsizing the federal government in the name of efficiency, led by the Department of Government Efficiency (DOGE). Efficiency in technical terms is about delivering the same thing with fewer resources. From what I can tell, T2 has no interest in doing the same things for less, they want to do less, regardless of the value it provides. This fact is evidenced by the number of workers with high marks in critical functions who were dismissed (see the stories on reddit’s r/fednews for anecdotes). Popular programs, like the National Parks, have seen significant cuts, potentially imperiling the park program entirely. If there is any analysis of how and why cuts were made, it has not yet been shared with the public besides claims posted by DOGE on X devoid of much context. More so, the cuts are executed with a certain callousness and cruelty for the people being shown the door.

Set aside the “efficiency” branding and ask—what exactly is the nature of what is happening in DC? A leading framework is a purge—removing bureaucrats that blocked the lawful authority of the president, draining the swamp, or ending the deep state. Choose your favorite euphemism according to your partisanship and mental wellbeing. makes this case in What I think DOGE is really up to. Yet even a purge feels odd—there is no ideological purity test. Many Trump supporters are getting shown the door. It does not matter if you share the same values, you are in their way—the wrong place at the wrong time. Ultimately, the Federal government will be permanently smaller for the foreseeable future, and DOGE’s actions have fundamentally altered the expected stability of a job in the federal government.

The messaging from the administration and their allies refuses to be pinned down to a specific strategy besides “America First” and “Let Trump Be Trump.” How that applies to any given scenario seems intentionally left to Trump’s discretion. The closest I have found to a success criteria for their decisions is from their supporters. Brad Gerstner is the founder of Altimeter Capital who invests in both public and private companies. He has professional connections into the T2 admin and is optimistic about DOGE’s long-run effects. He claims on his BG2 podcast that DOGE’s goal is to reset the size of the federal government to the baseline of 2019 and a standard growth rate, effectively removing the higher expenses and growth rate T1 and the Biden administration embraced through the pandemic. Gerstner argues that doing so could balance the budget by 2029, the end of the T2 admin. Respectfully, we had a stable National Park Service and PEPFAR in 2019. As of March 2, 2025, PEPFAR is apparently done, and the National Parks are in flux. While the overall size of federal expenditures may (and probably should) end up closer to 2019, even if they achieve this in scale, the funding mix and set of capabilities will be different. The character of DC as a city and as the seat of federal power and capabilities will be fundamentally changed by these events, which is the entire point.

What stands out to me the most about this are the tweets/posts from DOGE. The typical post includes details about contracts, waste, and sometimes a complete misunderstanding of what they are looking at. They get much smaller over time, starting with USAID and ending with b2b SaaS.

The posts transport me back to a place with their own rich history with a doge: Venice. Standing in the Doge’s Palace, the Venetians display huge paintings depicting themselves leading a Crusade against Constantinople. It has the distinction of being the only Crusade when Christians mostly focused on assaulting other Christians. The Venetians are extremely proud of this history, with the loot from it still prominently on display.

Rather than a purge, I have begun to wonder if a better framework for these events is a sacking. And when Venice sacked Constantinople, it did not get better. It permanently redefined Western civilization.

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The Sacking of Constantinople, 1204

The Sacking of Constantinople in 1204 was the culmination of the Fourth Crusade, a sequence of events that I consider the funniest time Constantinople has been sacked.

To set the stage, let’s start with the crusaders themselves. A bulk of the attacking force were French knights, though in this case they were on Venetian ships and under Venetian orders. As was common at the time, the French and the Venetians answered to different authorities simultaneously. Both acknowledged the power of the Roman Catholic Church, which in the Western countries made them Latins, referring to their status as the diaspora of the Roman Empire. When Pope Innocent III called for a crusade to retake Jerusalem via Egypt, the French knights answered. They contracted the Venetians to build their ships and carry them to Egypt. Besides the Church, the French ultimately answered to a monarch, but the Venetians answered to a doge, a democratically-elected ruler with relatively weak power.

The Venetians are funny in several respects. Venetian history is full of great stories for students of history like myself, though I found the actual city effectively dead and colonized by tourists. It is a pile of rocks across the mainland of Italy in a lagoon. It is a harsh place to survive, which is why the original Venetians went there to avoid Mongol invaders. They would live off the sea, its fish and its trade. What remains of Venice is a monument to their history as hilariously successful traders, pirates, thieves, and forgers. The fresco above San Marco’s Basilica commemorates them stealing the bones of San Marco (St. Mark) from Muslims. San Marco’s bones are on display now, though they were “lost” for a bit until “an angel brought them back”, leading one to suspect this might be a completely different Marco’s bones. As one of the naval superpowers of the region, they were one of a few suppliers able and willing to get an invading army to the Holy Land—if the money was good.

Uniquely, Venice was a republic and the doge (from the Latin dux for leader, which in English became duke) was their executive authority, albeit one with poorly defined powers. They had their own intentionally complicated system for electing the doge to try to prevent fraud and power consolidation, as well as a punitive system for poor leadership. If selected to be doge, one had to hand over all their assets, to be used as collateral against their own ineptitude. If the republic did not grow, their assets would be used to pay back the republic. The sitting doge could not invest their money during this time at all. The opportunity cost of being doge was so high that few of the elites even wanted to be doge, preferring instead to see to their fortunes while also trying to ensure no other family gathered too much power as doge.

The defending force was the also-Christian city of Constantinople, the seat of power of the Byzantine Empire for over 800 years at this point. The Byzantines claimed their own spiritual authority, as the capital of the Eastern Orthodox Christian Church, while claiming the title of the true heirs of the Roman Empire. There was truth to this claim as they had a direct lineage to Roman Imperial authority, though they lacked the ability to subjugate their neighbors the way the original Romans had. Part of this was due to a leadership style and system of governance that was so convoluted, the word “byzantine” is still used as a pejorative for an overly complex, opaque process. These were truly people that cared about process over outcomes. While this empire was in decline, they were an important barrier region between Christian Europe and Muslim Asia Minor.

As compelling as the whole story is, I want to isolate a few critical events and themes that resonate with the current situation:

Moral Justification: “They started it”

Tensions between the Latins and Byzantines had been high throughout the Crusades. The Byzantines found themselves trapped between aggressive neighbors, Muslims and Latins, who were both hungry for land, control of trade routes, and the symbolic power for their religions of control of the Holy Land. There had been skirmishes as the Latins traveled through Byzantine lands to Jerusalem. As Christians, the Latins expected their loyalty, while also deriding the Byzantines as too weak and accommodating of their Muslim neighbors to retake the Holy Land. That is why the Latins must do it.

In May 1182, 22 years before the siege, the Orthodox inhabitants of Constantinople attacked the Roman Catholic ones, in an event known as the Massacre of the Latins. The primary victims were Italian merchants that the Byzantines believed had accumulated too much power and wealth in their home. Political relationships between the Western kingdoms and Byzantine Empire had been tense since this event, with many Latins calling for revenge.

Trigger: Debt Crisis

Constantinople became the target of a crusade because a debt needed to be repaid. Doge Enrico Dandolo of Venice saw the crusade as a chance to get rich and had taken on a significant debt to finance building the ships for the crusade. The ships were ready to depart for Cairo on June 24, 1203, but the French knights who commissioned the ships could not pay because they had made a crucial logistical error. The Venetians would force them to repay by becoming their own private military, to be directed at whereve the Venetians believed would be most profitable. This targeting was despite the fact that, when the pope ratified the agreement between the Venetians and crusaders, he had explicitly banned this army from attacking Christian states.

At the beginning, when Pope Innocent III called for a crusade to retake the Holy Land, he was mostly ignored. The Germans were feuding with the pope, and the English and French were busy killing each other. The French would decide they would rather fight for the Holy Land than England. Having experienced both French and Mediterranean climates, I do not blame the French for shifting their focus, but it was not the weather they were interested in. The pious crusaders wanted to prove the superiority of Christianity to Islam, the greedy crusaders wanted the land and control of trade routes of silk and spices, and the bloodthirsty crusaders just wanted someone else to fight. To get there, they needed ships, and there were only a couple places that could provide ships in that quantity: Genoa and Venice.

Building a navy is expensive, in both real costs and opportunity costs. The crusade wanted transport for 33,500 people, which would take several years of the entire capacity of shipbuilding production from either city. Furthermore, the crusaders would pay upon arrival to board the ships, such that each city would have to go into years of debt for one customer who might not pay. Let’s not forget the crusaders would also show up armed to the teeth, ready for war, and potentially desiring a better deal. Genoa had no interest, but Doge Enrico Dandolo of Venice wanted to take the risk. He agreed to terms with the French knights and the pope.

Critically, the crusaders forgot to get a binding agreement that all crusaders would sail from Venice on these ships. Many departed from other ports, leaving only 12,000 to show up in Venice out of the 33,500 they expected. Worse for the ones who arrived, they could not pay in full. So the doge imprisoned them, then told them they would work off their debt by looting nearby towns…Christian towns. Towns that had been problems for Venice. Zara was a key target, having successfully rebelled against Venice in recent years. Some crusaders found this morally abhorrent and left, either for home or the Holy Land via other means. (Note: I have no idea how debt and contracts worked during this time, but presumably the Venetians had to decide if they wanted to fight the French crusaders to stop them from leaving. It might not have been a risk worth taking in the field.) The pope threatened leadership with excommunication. All the same, the crusaders sacked Zara, and the pope excommunicated them…via a letter that the Venetians promptly decided not to tell anyone about.

Leaders More Interested in Advancement than Governance

Constantinople became the target of this renegade crusade after Alexios IV Angelos, the son of a recently deposed Byzantine emperor, proposed they take back Constantinople, depose Alexios IV’s brother named Alexios III (everything with the Byzantines is this complicated), and put Alexios IV back on the throne. In exchange, he would pay the entire debt owed to the Venetians plus even more rewards. Alexios IV even offered the crusaders a way to repair their relationship with the pope, by offering to place the Eastern Orthodox Church under the authority of the pope. More French knights would balk at attacking Christians, taking some ships with them to attack Syria; but the Venetians loved this plan and bribed the rest to go along with it.

The infighting between Alexios IV and Alexios III was commonplace in the Byzantine empire. From 1180 to 1203, there were at least 4 different rulers of the empire, compared to the 2 leaders that had ruled from 1118 to 1180. During this time, Byzantine leadership was focused on their own survival by securing against internal threats and allies with riches. Expanding the empire, fostering trade, and even repelling invaders were all afterthoughts to getting power and keeping it.

The city would be sieged twice in as many years, with each siege itself an interesting bit of military history, defined by the city’s strategic location between the Black Sea and Mediterranean Sea. What ultimately matters is that the crusaders breached the walls in August 1203 and put Alexios IV on the throne without destroying the city outright. The city would have an uneven peace until the citizens of Constantinople deposed Alexios IV, whose usurper executed him before he could make good on his promises to the Venetians. The Venetians demanded their contractual payments from the city leaders. When the city leaders balked at paying them, the crusaders went back to assaulting the city in March 1204. It was not a certainty they would successfully breach the city, in part due to unfavorable weather, and priests had to fight low morale with claims that God was testing their resolve. However, when the weather turned, the crusaders would ultimately overwhelm the city by sea. That assault by ship is what the painting commemorates, the eighth day since their initial siege.

Looting and Pillaging

The crusaders sacked the city for three days. Eyewitness accounts point to ruthlessness towards the citizens, with widespread murder, rape, and theft. The city’s churches and monasteries were defiled and looted.

Notably, the Venetians took the golden horses that stood atop the Hippodrome and put them on top of San Marco to celebrate their victory. They are still visible at San Marco, but replicas adorn the roof while the originals are kept indoors to prevent any additional environmental damage.

The elites of Constantinople fled the city. Nicetas Choniates, an eyewitness who wrote about it afterwards, claims that the ordinary citizens were all too happy to see the incompetents driven off:

The peasants and common riff-raff jeered at those of us from Byzantium and were thick-headed enough to call our miserable poverty and nakedness equality...Many were only too happy to accept this outrage, saying "Blessed be the Lord that we have grown rich", and buying up for next to nothing the property that their fellow-countrymen were forced to offer for sale, for they had not yet had much to do with the beef-eating Latins and they did not know that they served a wine as pure and unmixed as unadulterated bile, nor that they would treat the Byzantines with utter contempt.

Source: Angold, Michael (1997). The Byzantine Empire 1025–1204. pp. 327–28.

Aftermath and Legacy

In the immediate aftermath, the French and Venetians would install their own rulers, and some would take lands around Constantinople. The Byzantine Empire lay in tatters, and former nobles had to decide how best to fit into the new political environment. Some would rebel, some would negotiate with the new rulers. Venetian rule would last for 57 years, before being deposed by Greeks, who would claim they had restored the Byzantine Empire. Constantinople itself was not dead, but it would never recover. The empire would struggle in the face of new challenges, including a plague and open war between the factions remaining.

Venice delighted in their newfound power. Their experience was one of victory after victory. Excommunication was a small price to pay to own an empire of land, trade, and control of the Eastern end of the Mediterranean sea.

The Roman and Orthodox Churches would schism over religious beliefs, power, and trust. No longer would Christians view themselves as simply Christian. After Constantinople, and long before the Protestant Reformation, the answer to “What kind of Christian are you?” mattered substantially in many places of the world.

Ultimately, Constantinople would fail as the European bulwark against Muslim Ottoman conquest of 1453, who would rename the city to Istanbul. Prior to their conquest, the citizens took comfort knowing their defenses, the Theodosian Walls, had withstood many sieges over a millennium. However, the walls failed in the face of a Islamic technological revolution: the gunpowder-powered cannon.

Constantinople’s fall put an end to any lineage of the Roman Empire. Their leaders had 250 years to fix their problems and never did, and the mortal wound was dealt by people they considered allies in a common cause.

Is America crusading against itself?

Maybe by now you have recognized some of the themes rhyming with modern times.

Moral Justification: “They started it”

The culture of suspicion and critiques between Latins and Byzantines is recognizable in our modern political landscape. Allegations that other citizens and allies are weak, effeminate, and requiring leadership would not be out of place on the Joe Rogan Podcast or other right-wing podcasts that fixate on soyboys, alpha males, Europoors, and chads. Perhaps a little on the nose for this piece, Secretary of Defense Pete Hegseth has the crusader rallying cry, deus vult or “God wills it”, tattooed on his bicep. The phrase exists in modernity in a superposition of religious fervor, macho signaling, cultural identity, literal threat, and white supremacy that has the useful quality of collapsing upon observation into whichever framing is most expedient. Like the Latins, strength, action, and conviction of purpose are core ideals of Trump’s movement.

Specifically though, DOGE’s actions to date are fundamentally about revenge in the form of ending careers. For example, there is only one FBI. An agent removed from the FBI cannot sell their services and expertise to the next FBI. They have to take their skills to the market and possibly retrain to suit the market’s needs and their career goals. Their career is effectively over, and they must find a new path.

One does not have to look far into the past to see a time when Trump’s supporters’ careers were threatened by political rivals. I have no interest in making this a culture war blog, but I will broadly highlight there was a culture war, people launched moral crusades to end jobs for an increasingly blurry line of actual sexual assault, bad behavior, morally repugnant opinions, and finally just bad opinions that are constitutionally protected speech. Turnabout is fair play, and just as many crusaders wanted revenge, DOGE wants blood for blood.

Trigger: Debt Crisis

For the Venetians, the debt was an opportunity. The leverage over their debtors let them settle old scores and flip the balance of powers in the Mediterranean. To do so, all they had to do was overlook morality, the value of allies, and a shared strategic goal of checking Ottoman i.e. Muslim expansion. In the immortal words of C. Montgomery Burns: “Family. Religion. Friendship. These are the three demons you must slay if you wish to succeed in business.”

The French crusaders were pressed into a war they did not expect, due to a debt others agreed to, for a world that would never come to be. As a Millenial, I get it.

The US has an unfolding debt crisis to the tune of ~$36 trillion, created by unsustainable national expenses, slow growth, and high interest rates to keep inflation in check. When the US had low interest rates and low inflation, servicing that size of debt was simple. But with higher rates, paying the interest will begin to take up a disproportionate part of the budget. The debt is real and is the motivating factor for DOGE’s efficiency drive—the debt sits at 13% of the national budget, just 1% behind what the US spends on Defense. Most critiques of DOGE center on the fact that most of the budget goes to Social Security, Medicare, and National Defense, which are politically difficult to reform, let alone reduce. Federal employee compensation is 4.3% of the budget, though they would not have much to do if the government only paid their salaries and did not give the other resources to do their jobs.

Perhaps unsurprisingly, Donald Trump once proclaimed, “I’m the king of debt.” Concerns about government spending were a moderate factor in this election with 45% of right-leaning voters citing it as “extremely important” to left-leaning voters’ 16%. As of March 4, 2025, popular support for DOGE remains high, as the public questions the utility and prudence of government spending. Dealing with debt responsibly is never fun, and it forces conversations of priorities, waste, and lesser evils.

Leaders More Interested in Advancement than Governance

The Venetians and Byzantines both shared this characteristic, but it was fatal for the Byzantines. It strikes me that the Democrat political party and the leadership of Federal departments found themselves in similar positions.

From personal experience with federal employees and contractors at Government Owned, Contractor Operated (GOCO) departments, there is an intense lack of confidence in leadership. The mission and stability of these jobs attract idealists, but the fact that it is nearly impossible to get fired also attracts workers aiming to do the bare minimum. They are often the first to complain about how much bureaucracy restricts their ability to do a good job. Leadership often does not want to expend the political capital to remove them, and productivity drags. There are also limits on promotions and salary increases. Do an OK job? 2% raise. Do a great job? 2.5% raise. Performing on par with someone 3 pay levels above you? It is faster to quit, take a job elsewhere, and get hired back at a higher level than to go through the normal performance process.

When I step back to the entire Federal apparatus, I see these self-inflicted wounds everywhere. Permitting and Defense Acquisitions are problems that can be fixed with a stroke of a pen, yet there was no leadership to do it. Everyone plays the game to stay in the game, even if they hate the game. Because if you leave, you can’t change anything, but you may also end up doing things that you are not proud of, like the French knights pressed into service.

This critique of the federal culture as a Byzantine creation seems increasingly bipartisan. served as Deputy CTO under President Obama, helped found the US Digital Service, and served on the Defense Innovation Board under both Obama and Trump. She reviews Why Nothing Works by Marc J. Dunkelman, which chronicles progressive’s mistrust of power and the stasis that has resulted from emphasizing complicated processes over desirable outcomes. In this quote, she is synthesizing conclusions from Dunkelman with her own thoughts and another upcoming book, Abundance, by Ezra Klein and Derek Thompson:

“Yes, we’ll need profound changes in things like the structures that allow for public participation. But I think Dunkelman is right that it has to start with the left challenging its own conventional wisdom. As Ezra Klein and Derek Thompson write in their upcoming book, “What is needed here is a change in political culture, not just a change in legislation.” I’d add a change in bureaucratic culture, even knowing how hard that can be. And it’s particularly hard right now.”

Especially in a republic, if the system is not working well, the constituents will notice. If people are still getting promoted without meaningful, positive change, you get a situation like the citizens of Constantinople spitting at the nobles as they flee the city, unaware of what was to come.

Looting and Pillaging

While there is plenty of cruelty towards rivals and leveraging rival’s tactics against them, it is not actually looting. What is explicitly looting is using government funds to profit yourself. There is no evidence of that.

Modern Lessons From Ancient History

Here is where I give a big disclaimer about ancient history: the people of the 13th Century are very different. Their cultures, values, and priorities differ immensely from our own. Periods of great conflict are useful only in as much as they amplify human nature, which does not change. The themes and decisions resonate with modern times because we share that nature with them.

I do not truly believe DC got sacked. Resetting the executive branch has far more in common with the American tradition of the “bloodless revolution” that shocked the world when the US successfully switched parties in power without a war. Waging war followed by mass executions and rape are categorically different way of changing leadership, which is a major reason the founders endorsed a system that could reform itself. Indeed, self-reform is the key lesson.

At the moment, DOGE seems to have hired a bunch of brilliant people then proceeded to start a wildfire, mindless yet cruel, consuming whatever it can touch. Right now, the Kalshi prediction market expects DOGE will save $1 billion by the end of 2025. Note that it is a net figure, such that any increases in spending elsewhere would offset DOGE cuts. By the end of 2029, Kalshi predicts spending will be $447 billion lower. Recall that the national debt is ~$36 trillion. The expected benefit of this revenge-fueled period for Americans remains elusive.

And yet the analogy of a sacking works. DOGE’s wildfire has left the US in a position of vulnerability, while its proponents revel in their revenge against fellow citizens. That is why the Sacking of Constantinople echoes so loudly in my head. The FBI and Department of Justice are seeing immense layoffs. A pivot towards Russia in diplomatic orientation has former allies wondering if they still are, in fact, allies. Singapore believes the US has pivoted from a force of “moral legitimacy” to “a landlord seeking rent”. While the CDC performed dismally in the last pandemic, my confidence remains low that the country is better situated to deal with one, especially one more lethal than COVID-19. In fact, a measles outbreak has already claimed a child’s life, the first time in a decade. The Atlanta Fed projects GDP to contract 2.8% this quarter, an outlier among forecasts at the moment but an ill-omen. The executive branch has disrupted itself, leaving not just DC, but an entire nation on edge and wondering what happens next.

Coda

The sacking of Constantinople is famed among history buffs because it marked the end of the medieval period and the start of the early modern period—it certainly seems likely this is a similar moment. It was extremely bad times for the citizens of Constantinople-then-Istanbul, creating entirely new risks for Europe. One interpretation of the Fourth Crusade is that this is just the blueprint for how tribes split, an end state of polarization when the in-group becomes the out-group, the bonds dissolve, and an empire ends.

Like Constantinople, there is a lot of blame to go around for how the US reached this point. Trust is low, adding a level of difficulty to building newer, better social institutions. I am skeptical that the man holding the knife can build anything that requires trust and buy-in from the whole country, though it would not preclude him from improving the efficiency and productivity of whatever persists. There is one version of this that looks like the looting of Constantinople, chiefly if government contracts are directed only at allies of the administration's companies. In that circumstance, expect to be greeted without any assumption of goodwill by the public, regardless of the quality and need for those products.

But we are not them. In the immortal words that echoed across time via a bootstrap paradox:

The people that stand out the most to me in the saga are the leaders of the Byzantine empire, who had 250 years to reform themselves and never did. Their decline made space for new institutions better suited to the challenges of the new era, leading to the Renaissance and Enlightenment eras whose ideas still shape modernity because they work. We either build those institutions now, or they will be built by others on the grave of our civilization.

I do not think we have 250 years to fix our problems—a rival will force a crisis far before then. It is difficult to believe that the country could or would mobilize to face a crisis when trust is this low. And that is where we have to start. I put my faith in the American people by extending them grace. Grace in their mistakes, grace in parsing their actions, words, and intent, and grace in victory and defeat. I do not believe Trump values grace or magnanimity, but I do believe his administration can still help Americans in practical ways big and small. (May I suggest automating taxes for people with simple taxes?) But grace in America is up to you and me. I know some people involved in T2, and I know more of their supporters. I trust their values and their competence, which gives me some confidence for the challenges to come, though I question the administration’s judgement. As I wrote this, T2 seemingly shifted into a new phase of the mass firings, removing authority from DOGE and putting it in the hands of the Cabinet members. Hopefully, the revenge phase of the siege has ended.

As for the administration, get on with the creative part of creative destruction already. How will history remember you? As the proud Venetians, enriching yourselves through self-interested destruction, the wildfire that sets the stage for others to build on? The weak, infighting, scheming leaders of Constantinople that brought about their ruin? Or something new?

Ultimately, we are still living with the consequences of what happened in Constantinople in 1204—the Eastern Orthodox and Roman Catholic churches never reconciled, Istanbul’s status as Europeans remains debatable, and you still probably shouldn’t go into debt with a Venetian.

When I ask T2 supporters how to understand the last few months, the answer I hear is, “In the end, this pain will be worth it.”

What rings in my ears are Alan Moore’s words from Watchmen. After completing a conspiracy to kill millions in the belief it will save billions, the antagonist Adrian asks a character cursed to see all of time, Dr. Manhattan, if his destruction was worth it, in the end. To which Dr. Manhattan responds:

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Thanks to , , , and for feedback on drafts of this work.

Maverick was an American beagle who became the first dog to live on another planet, Mars. She traveled with her owner Emil V. Feliz from Earth to Mars upon Voyage 117 of Starship 320.

Maverick was born and raised as part of a select pool of beagles that were candidates to form the first dog population on Mars. While some derided this project as a waste of resources, proponents argued successfully that such animals would improve mood and reduce instances of depression in colonists suffering from ‘dead world syndrome’ (DWS). In simulated DWS environments on Earth, dogs generally and beagles specifically proved the most effective antidote to the isolation of Mars. As a result, Experimental Cluster 28 was planned around accommodating a small pack of beagles, though an initial female beagle was required due to the limitations of artificial wombs.

Transferring a dog to Mars was met with fierce resistance from activists intent on preserving Mars’ environment and, allegedly, Martian dependence on Earth, directly leading to the foundation of rival groups: the Intergalactic Kennel Club (IKC) and the Friends of Mars.

Maverick would escape Earth, travel to Mars, and live until age 20 Earth-years there before passing away of natural causes. Maverick’s habitat hosts a monument to her impact on the people living off Earth. Most Martian breeds descend from Maverick in some capacity, as well as many dogs bred for spacefaring craft.

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Early Life

Maverick was born on Earth as a test candidate in the Intergalactic Kennel Club’s Neighborhood Walk program. She was born fourth in a litter of eight.

As the Neighborhood Walk program progressed, her litter was subject to intense scrutiny from the activist group, Friends of Mars, whose stated mission was to mitigate Earth-based risk to the newly settled planet. Their primary concern was forward contamination, long the domain of the Committee on Space Research (COSPAR) by the International Council for Scientific Unions (ICSU). After the discovery of the long extinct Ares microbe (see: Martian life before colonization), Earth had placed strict protocols to ascertain any continuing life on Mars. When COSPAR allowed the first bee colony (see: Origins of Martian farming, biological pollination), dissenting members sought to reorganize the body around policies that emphasized more complete understanding of the risks of organism transfer. Their policy called for a blanket ban on new organism transfers until there was certainty Mars had no indigenous life.

“[Friends of Mars] wanted [the IKC] to prove a negative. We’re still finding new life tucked away on Earth—how the hell would we ever show there was no life anywhere on Mars? It had been 50 years with no life detected anywhere near our colonies, any research outpost, or any automated drilling platform. Enough was enough.” -Victoria Deschains, first president of the IKC

Earth regulators had adopted protocols in accordance with this precautionary principle to prevent forward contamination, angering residents on Mars who saw this as lacking in evidence, an obstacle to self-determination, and actively harming current residents suffering from DWS. Despite activist pressure, including activist attempts to cut off the power to the breeding facility, unfounded accusations of mistreatment, and one unsuccessful attempt to poison the dogs, the IKC continued to prepare for a beagle transfer

Because of escalating pressure, however, Maverick and the other test candidates were moved to a remote, confidential location for further testing and preparation. The location is still unknown but is believed to have been near Jupiter, Florida, Earth.

Selection Process

“We needed a dog that could be an entire planet’s best friend, and Maverick was.” -Victoria Deschains, first president of the IKC

To address DWS, psychologists examined the effects of both cats and dogs. Cats had demonstrated effective companionship, were well-tempered in confined quarters, and, due to their independent nature, were considered ideal potential companions for the long journey. However, engineers were intimidated by the design requirements of trying to isolate every life support system from cat’s natural curiosity, agility, and propensity for exploration. Early attempts at bringing cats into orbital environments with simulated gravity also revealed cats were highly attuned to their environments and exhibited signs of extreme stress, despite showing no signs of stress in confined environments on Earth. While these traits were eventually bred out of cats for spacefaring, the early settlers elected for the path of least resistance.

Dogs presented simpler design requirements and also exhibited extremely robust treatment for DWS. With replicated results across different dog breeds, the IKC set out to select breed test candidates for Mars. Breeds and specific dogs would be judged on their disposition as defined as:

While no dog breed represented a perfect mix, the leading breeds for study were the Bichon Frise and Bolognese. Bred for hunting, beagles were in a secondary tier due to their shedding, need for exercise, and louder vocalizations, as well as a general ‘mischievous’ nature. Their status was elevated for testing when it became apparent that their propensity for mischief was tightly correlated with the strength of bond formed between the humans and the dogs. When the IKC reported the results of their research and the environmental design requirements for beagles were demonstrated to be feasible, the settlers of Olympia, Mars voted overwhelmingly for beagles as the first choice.

Emil Victor Feliz of the IKC was Maverick’s handler. Martian protocol for organism transfers at the time called for an organism and a handler to travel, and another permanent settler to be trained for emergencies. When Maverick was selected as the lead candidate, Feliz accepted an invitation to become the planet’s first veterinarian, breeder, and zoologist. Intended as a permanent settler, Feliz’s role on Mars would be to ensure Maverick’s successful integration into the colony, manage her ongoing health, train both the AI and an apprentice, and facilitate embryo transfer to expand the dog population on Mars. Given the controversy on Earth, Feliz would also have to facilitate getting her safely from the training facility to the launchpad. He would also be responsible for recording footage and providing commentary about her life for the television series IKC produced during this time, Beagles in Space, to defray cost of research and build public support for the project.

“Going to Mars would be the last great adventure of my life. When my wife passed, I knew I needed to commit my remaining years to something greater than me. Maverick was the best companion you could ask for, and helping to bring her boundless joy to Mars was the best choice I could have made.” -Emil Feliz

Preparation for Life on Mars

Maverick’s litter was the third generation in her line selected to show little stress in contained environments, limited vocalizations, and extremely easy to train. Maverick spent her first year in training and evaluation before being selected for travel. While still restricted from traveling to space, each of Maverick’s litter prepared in environmental training centers with habitats similar to Starship 320 and Experimental Cluster 28.

Maverick’s litter demonstrated three test candidates, with Maverick having the highest scores in reproductive fitness and therapeutic power for DWS. When it became apparent that several candidates would achieve key benchmarks for overall wellness, reproductive fitness, and temperament for space travel, COSPAR knew they would have to make an active choice to approve or decline Maverick’s transfer license.

The IKC and Martians appealed to COSPAR to license Maverick’s transportation. COSPAR scheduled a meeting to discuss, but key staff aligned with Friends of Mars did not attend. Lacking a quorum, COSPAR could not issue an official verdict. A press release from the Friends of Mars lauded the dissident members and declared that, by blocking this transfer, they had successfully preserved the planet for future generations

“What’s the point of making life better for people if we risk ruining the planet forever?” -J. Akeep, founder, Friends of Mars

Voyage

With COSPAR de facto blocking Maverick's transportation, the IKC had to secure other passage for both Maverick and the cryogenically frozen beagle and beagle-mix embryos for the breeding program. While COSPAR could effectively prevent shipment among sitting members of the UN Security Council, younger nations sought independent launch capabilities free of the military obligations of such tools, as well direct trade relationships with Mars. Therefore they had been slow to sign on to COSPAR restrictions, strictly avoiding nuclear weapons programs, and had been soliciting partners to bring purely civilian technology to their countries. Hoping to be the preeminent spaceport for Africa, Kenya had signed a long term contract with LoudElevators, an orbital delivery service licensing Starships, to provide launch services at Nairobi Space Center.

While Feliz never confirmed the dates or departure location, it is suspected that Maverick left aboard one of the Kenyan launches on 31 October 2157, aged 2. Feliz confirmed that Maverick was sedated for the trip, as “the launch was probably the most terrifying thing I’ve ever done, much scarier than landing on Mars. Of course, any launch would terrify a dog, and we didn’t want to put her through that; but I knew it was a young space center without much track record and a ship built in zero gravity. They did alright though.”

IKC president, Victoria Deschains later defended her decision to GNN, saying:

“They wanted things to stay the same, they were terrified of extreme outcomes without any evidence, and there was so much good that could come from it. ‘What right did I have to send the dog to Mars if all of Earth wanted to stop it?’ For one, it wasn’t all of Earth, I sure wanted to and plenty of others did too. Dogs and people co-evolved, we belong together, even in the stars, and Mars proved it.”

Maverick awoke from sedation in good health after the rendezvous with Starship 320 for its 117th Voyage. The craft had recently been renovated to support 1G with complete radiation shielding, hard requirements for the IKC to initiate a dog transfer. Additionally, it hosted an IKC-designed living quarters suitable for the dog’s and handler’s requirements, wellness packs that Loyal, the premier animal longevity research organization, predicted would extend Maverick’s life to a full 20 Earth-years, and emergency veterinary equipment. The major difference from the IKC kennels was studio equipment, as Feliz was responsible for streaming their voyage for the series Beagles in Space, where they filmed for 1 hour every 24 hour period of their 4 month journey, routinely drawing 10,000 live viewers. Their landing on Mars was the most viewed event in Mars history at that point.

Life on Mars

Maverick was an instant celebrity on Mars. After landing, Maverick was transferred to the space port, where she would be most comfortable but not before dipping her paws in an ink to mark the first dog steps on Mars. From Olympia Space Port, she traveled quickly to Experimental Cluster 28, colloquially referred to as the ‘dog house’. Envoys from different colonies had gathered to greet her, with several native Martians reportedly overwhelmed with emotion at seeing another mammal on Mars, with several stepping outside the habitat to compose themselves. As a result, basic training was put in place for new visitors about how best to interact with a dog, and Feliz would continue to provide oversight to all meetings.

On Mars, the IKC worked with Feliz to carefully balance her schedule. Maverick had short-term obligations as a symbol of the success of Martian colonies and an actual therapy for DWS patients, while also representing the key breeder for a multiplanetary canid species. Maverick would visit Olympia, Musktown 4, and New Hong Kong (see: Harmony, Secession and Refounding) before the first artificial insemination. While she did not travel during her pregnancy, many visitors visited the dog house to view her playing. Within the first month, reports of DWS were down 40%. Her living quarters would remain a popular destination for school field trips.

Maverick’s persistent popularity surprised Feliz. “I thought things would die down after we landed, but it was really just the start. Seeing a dog on grass on Mars was surreal for me, but Maverick may as well have been a furry alien for the natives.” -Feliz, Maverick’s handler

Maverick would ultimately have 8 litters resulting in 24 pups. Designing her litters required balancing political pressure for each colony to get their own beagles, introducing genetic diversity, and the availability of facilities to host different kinds of dogs. Maverick’s only health issue surfaced as an adult with a crack in her canine teeth, requiring titanium crowns that became a signature.

Death and Legacy

Maverick’s life and death opened a new age for human space exploration: non-human companionship. Maverick’s journey was the result of decades of engineering and policy work that ensured not just humanity’s survival but the wellbeing for people, animals, and extraplanetary life.

“It wasn’t all rainbows. People were still people—plenty of ink has been spilled about the accidents and the chaos around people wanting to bring their own dog home. And we could have probably spared ourselves a lot of headaches if we got less mischievous dogs than beagles. But the bond between people and dogs predates language. How could our future not be together too?” -Victoria Deschains, founder of IKC

Maverick would breed until she was 12 Earth years, when the IKC ended the Maverick breeding program because concerned for her health, though her energy never flagged during this time. Over that decade, IKC guidelines had become adopted into standard Martian architecture, such that most facilities were suitable for dogs, though some habitats restricted access. Maverick would continue to live in the dog house with many of her puppies until passing of natural causes at age 22.

With a stable dog population on Mars, Earth countries would relent and several other dogs would ultimately travel to Mars, typically as a luxury companion for tourists and colonists, though some were sold for trade. Still, Maverick left an indelible impact on Martian culture, with monuments to her presence on Olympia, New Hong Kong, and Musktown-14. Many of her shed hairs remain family heirlooms, and most Martian dogs trace some lineage to her.

Maverick is widely attributed to be the reason that beagles are the preferred companion for starship captains and the traditional first animal to step foot on planets beyond Sol.

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Thanks to Emma McAleavy, Paige Lambermont, and Andrew Miller for their feedback on drafts of this post.

There is an immense supply of biographies documenting the personal achievements and failures of great innovators like Jobs, Musk, Rockefeller, Grove, and Ford. They all have much to teach. But given the divisiveness of our era, I felt called to look back home: Alexandria, VA, the hometown of yours truly, Robert E. Lee (yikes), and George Washington.

Washington is a mystery to me, and apparently that is intentional. The young country needed an icon to embody its ideals, and he was all too happy to step into that role, often literally rewriting his own personal diaries. He wasn’t a political genius. He wasn’t a great military leader. His speeches are considered stiff, and he was extremely self-conscious about the simplicity of his education. Though he is an icon of liberty, he owned slaves all his life. How does one reconcile the reality of the man with his legacy? And what does his life and learnings teach us about material progress?

Those claims among the others I will make here are drawn from Joseph Ellis, a Pulitzer Prize winning author, who fortunately had the same questions. In fact, as I learned in the opening pages of the book, Alexandria is also his hometown. We even went to the same grade school in Old Town, St. Mary’s, albeit 30 years apart. His book on Washington, His Excellency, is something of the last word on Washington, as a batch of his correspondences were discovered and shared that historians assume must be the last remaining unknown letters. Thankfully, he did not approach this as an academic, but rather a rigorous summary of the most important elements of Washington’s life and historical consensus possible in 200 pages.

In the same vein, this post is not a book report, but an attempt to answer a few questions about Washington’s life that illuminate our own era:

1. What radicalized Washington against England?

2. What was Washington’s personal dream for America?

3. How do we reconcile Washington’s personal failings with his achievements?

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What radicalized Washington against England?

There are many modern analogies between the colonial-era US and modern day. Many founding fathers were notorious shitposters, complete with anonymous profile pics and shifting accounts. As far as Ellis details, Washington never engaged in that particular domain; but he bears another hallmark of the internet age: he thought a conspiracy was out to get him.

Understanding why he saw British conspiracies behind every maneuver requires some understanding of his background. As the son of a middle-class family, Washington grew up in a position with which many middle-class Americans of today might sympathize: respectability and poverty both seemed equally possible. Washington was very much a striver for respectability (and would flip his shit at anyone who called him out on it). His endeavors before the Revolutionary War are fascinating, especially how he accidentally started the French & Indian War, but suffice to say, he married into respectability and wealth. The trick is that he was a steward of his wife’s fortune, and he could not use it unilaterally. Rather, a network of suppliers to his wife’s family would enact his requests and reject any they thought were not in her interest. (In my head, this entire incident plays out like an episode of It’s Always Sunny in Philadelphia).

One of those suppliers was a merchant in England. At this time, Washington’s only revenue came from growing and selling tobacco. And a respectable Virginia gentleman would grow the finest tobacco, and sell it in England through a trusted merchant, in this case a merchant called Cary & Co. The firm had a long history with his wife’s family, and extended that service to Washington. A respectable Virginia gentleman would also outfit his estate, his family, and himself with the best products from England to flex on the country bumpkins, so the same merchant would receive a big list of stuff to buy from the best shops in England for his estate, his family, and himself. Many Virginians played this game, and almost all of them ended up in debt to merchants.

What radicalized Washington was this trusted merchant, constantly telling him the prices of the goods he had to sell and the prices of the goods he asked them to purchase moved against him. Ellis includes an aside investigating if they really were screwing him, and the historical record points to no. Instead, the British empire had successfully grown tobacco in India, and the market was flooded with supply. Regardless, Washington was ignorant of the Indian supply but extremely aware that he was headed on a path of permanent indebtedness.

“The more Washington thought about it, the more he concluded that no amount of diligence on his part, no spell of excellent weather, no favorable fluctuations in the tobacco market, could combine to pull him out of debt, because the mercantile system itself was a conspiracy designed to assure his dependency on the likes of Cary.”

You don’t have to squint too hard to see how familiar this arrangement is to anyone who dreams of owning a house in California.

After Washington saw the mercantile system as his enemy, he changed his entire estate. He treated British proclamations with mistrust, intended to enrich themselves off the colonists’ labor, specifically the Stamp Act and the proclamations from the king that the frontier was closed to settlement. Far from protecting the peace between colonists and natives, he thought the British ruling class was simply protecting the land for their own interests. They likely were, and Washington likely knew this because it is what he might do in their stead. Ultimately, he saw an economic system designed to enrich the powerful and impoverish everyone else. The mercantile system was zero-sum, a system of victims and victimizers. He did not want to be a victim of history (a theme of America’s beginning we will return to), so he changed his entire business model to support local industry. He changed his crops to food for trade in the colonies, and he set to work building ships to support local trade. He vertically integrated his estate to avoid being reliant on anyone else.

What was Washington’s dream for America?

In short, Washington wanted self-determination. He wanted a fair system for distributing the country’s resources. There was no question of if it belonged to the natives:

“He regarded the Indian tribes of the region as a series of holding companies destined to be displaced as the growing wave of white settlers flowed over the Alleghenies. There was nothing right or wrong about this development, as he saw it. It was simply and obviously inevitable. The Indians, understandably and even justifiably, would resist. After all, they had dominated the region for several centuries. But they would lose, not because they were wrong, but because they were, or soon would be, outnumbered. (Later on, during his presidency, he would attempt to guarantee tribal control over Indian enclaves, his effort to make a moral statement amidst a relentlessly realistic diagnosis of the demographic facts.)”

Ellis makes the case that Washington “instinctively understood the core principle of republicanism, that all legitimate power derived from the consent of the public”. Washington rarely used the term republic, but would refer to the American empire that called for both conquest and a strong executive, a consequence of his efforts leading the Revolutionary army that required unity of command i.e. the army can’t work with multiple people claiming authority and giving orders. The country could not either, no matter how much Jefferson and Southerners dreamed of an agrarian utopia where power is never concentrated.

As soon as the Revolutionary War ended, Washington felt the country was on the clock. The British maintained control of Canada, and they would not forget the possible riches of the New World. The young country must establish itself as an identity unique from the Old World. It must find a way to integrate the immigration into the country that makes it stronger. In fact, the Old World could only weaken the country. Far better to disavow any foreign alliances in order to avoid the conflict and zero-sum thinking of the wars of conquest fought there. Europe had no answers for its own desperate people, and the rulers there were only ever looking to use people e.g. the mercantile system.

Washington’s event horizon was the settlement of the Americas. He had no dream besides keeping the country going as an independent, contiguous entity, free of European interference. He could not forecast specifics—he had several misguided beliefs about how important Virginia would be to its future, including an incorrect belief that Virginia must have the most economically important waterways. Rather, his emphasis was on establishing America as independent and a nation i.e. a strong federal government and a national character binding Americans together.

Washington desired a country with talent and a sense of personal honor. His own attempts to emulate this looked like a king of a small country but with the assent of the people rather than a monarch or religious figure, who ruled because he was the best of them. In practice, it meant you had to be educated enough to know all the ways democracies fail, smart enough to figure out practical solutions, and command the respect of the public. For example of how talent mattered, consider an episode during the Revolutionary War. Frenchmen kept showing up claiming to be aristocrats and demanding to be generals to lead this American rabble. (The American experience of being lectured by Euros that think them backwards and in dire need of education and leadership is not unfamiliar—consider the modern UN, climate conferences, NATO leadership, etc.) Marquis de Lafayette arrived at Valley Forge in a similar fashion, right as the Revolutionary Army nearly came apart. In contrast to his countrymen, he asked to serve at any rank in the most dangerous missions. Washington immediately recognized he was different. His resourcefulness, commitment to high standards, and bias for action would earn Washington’s admiration, eventually becoming effectively an adopted son to Washington.

Washington believed in ordered freedom—freedom that brought chaos was no freedom at all. This sentiment was borne from his own experiences in the colonial army. He was entirely reliant on the Continental Congress to provide his funding, and it rarely provided it on time or in the amount promised. He saw the Articles of Confederation fail for the same reason. After Shay’s rebellion, when the states lacked a coordinated response to a farmer’s uprising, it became clear the country wanted to reassess the Articles of Confederation. Desiring legitimacy for a new set of national laws, states asked Washington to lend his war hero reputation to the cause. Washington refused any association with the effort until he had secured assurances that states were ready to seriously address the issue.

Washington desperately wanted the leaders of the country to be brothers in this endeavor, with the president being revered, such that no one would dare criticize the president’s choices or expect the president to address criticism. This hope vanished by the end of his second term. Jefferson and Madison were already slandering the policies championed by Washington and Hamilton, as well as Washington personally. They started anonymously and gradually became more visible, a rift he finally acknowledged but regretted that the norms now allowed the president to be criticized, that the country became so quickly divided into parties, and that his friends and subordinates could not agree on anything but his unique leadership capabilities.

In summary, Washington cultivated strength in the present facing an unknown future. He sought unity, integration, and a system that would fully ensure America would not be a victim to one of the imperial powers. Accomplishing that required effective coordination between the states, effectively integrating the desperate people from the Old World, isolation from European affairs, and time to cultivate the capability to resist future imperial incursions. Implementing this strategy would require new thinking from talented individuals who embraced the responsibility of securing the nation’s future.

How do we reconcile Washington’s personal failings with his achievements?

In the summer of 2020, when Black Lives Matters protestors physically attacked monuments of the country and ideologically assaulted the foundations of the country, Washington was frequently presented as one of a corrupted, mediocre man who's only defining characteristic was being white and in the right place at the right time. In many ways, my interest in Washington was a reflection that this was stupid and intentionally misleading.

Of course, it is true that the young country needed a myth, and they chose Washington. Building the idea of a nation was essentially one giant psy-op on barely literate people, and one that Washington embraced. At long last, he had respectability; nobody needed to know about his missteps because, of course, he had never had any.

Ellis is unflinching in peeling back this mask, often in very funny passages, but most frequently in documenting Washington’s history as a slave owner.

All his life, Washington owned slaves. When he went to war, his slave servants went with him. Washington accepted free blacks in the Continental army and commanded a racially integrated army. Washington endorsed the idea of extending freedom at the end of the war to any slaves in occupied South Carolina that took up arms against the British. As a Virginian, he was culturally surrounded by other slave owners. His tobacco farm was economically dependent on slave labor. When he married his rich wife Martha, her estate brought many slaves. Their slaves intermarried at Mt. Vernon.

Slavery was a weight on Washington’s mind. Lafayette told Washington the end of slavery must be a natural conclusion of the ideal of liberty at the heart of the American Revolution. After ending British rule in the US, Washington became the focus of an abolitionist campaign to show the US really did value freedom. What better way than having their icon free his slaves? Robert Pleasants, a Virginia Quaker, emancipated all of his slaves and implored Washington to do the same. Anticipating an exercise like this one, Pleasants predicted it would haunt his reputation forever. Quoting Ellis quoting Pleasants, “How sad it would then be to read that the great hero of American independence, “the destroyer of tyranny and oppression,” had failed the final test by holding “a number of People in absolute slavery, who were by nature equally entitled to freedom as himself.”

Washington ignored the letter, but supported other emancipation efforts. He told the Virginia legislature he supported a motion to allow emancipated slaves to remain in Virginia: “I can only say that there is not a man living who wishes more sincerely than I do, to see a plan adopted for the abolition of it [slavery]—but there is only one proper and effectual mode by which it can be accomplished,& that is by Legislative authority: and this, as far as my suffrage will go, shall never be wanting.” He denied payment in slaves: “I never mean (unless some particular circumstances should compel me to it) to possess another slave by purchase; it being among my first wishes to see some plan adopted, by the legislature by which slavery in this Country may be abolished by slow, sure, & imperceptible degrees.” And yet, he still owned slaves.

One explanation is that the economics of slavery for Washington had changed. Remember how Washington abandoned the tobacco business because it was putting him in debt? The new crop (mostly wheat) and shipbuilding business did not require anywhere near as many slaves. Now, they were mouths to feed. Washington debated selling the slaves, not freeing them, but even then, he encountered overlapping concerns. For one, he did not own Martha’s slaves. In fact, Martha did not really own her slaves either; they were property of the estate. They were both overseeing the estate, but they could not legally liquidate its property. Only Martha’s son could do that when he inherited the estate. Second, Washington’s oldest slaves were past their prime working years. Third, and as Ellis claims most importantly, the slaves of the different estates had intermarried at Mt. Vernon. Washington had resolved not to break up families, making selling any large population difficult. His only way out was broad emancipation, as Pleasants asked. Instead, he “vowed never again to purchase another slave”, which rang hollow because his slave population was already economically a drain. Ellis makes the case that Mt. Vernon ran a deficit and effectively became a slave retirement home and child-care center, “who he was morally obliged to care for.” Washington would ultimately state in his will that all his slaves would be freed when Martha died, ensuring the families would not be separated. These were victims of history, his victims, but it is difficult for me to say he did not take this obligation seriously, even if he ignored Pleasants’ just solution.

In my mind, slavery is an entirely separate category of personal failing than others, but there were others. It is worth acknowledging the other issues to understand the man. Ellis’ goes to lengths to give a sense of who Washington really was. He was obsessed with acquiring land. He was a screamer, known to flashes of anger where he would simply unload on subordinates. To his credit, as he grew in stature, he knew he had to control this and developed a strict discipline to hold his tongue. Washington really pressed the limit on what he was supposed to be doing with Martha’s money, with merchants occasionally pushing back. Men in his family tended to die young, and he expected to follow them into the grave. When he retired from the Colonial army, he was convinced he would die before the country would move on from the Articles of Confederation. This sullenness prevented him from investing much in the country’s success, until his associates told him he would be needed again.

Washington and Progress

A recurring theme throughout Washington’s life is the victims of history. Slaves, natives, and the poor immigrants from Europe were all victims, desperate for a better life. Washington was nearly made a victim himself and seemed willing to victimize others (slaves, natives, and even other colonists) to avoid it. Washington’s enduring contribution was implementing a system that could end victimization by ending desperation. Simply having a system that allowed for integrating different cultures in a way that everyone could feed themselves was revolutionary in his era. Having a strong federal government set a baseline for how people could be treated in a region, a revolutionary idea, and a persistent failure point in the later French Revolution. What makes Washington stand out is that, for once, the tide of colonial victimization could be changed, albeit imperfectly. America’s founding ideal, then, is not colonial victimization but progress. The Industrial Revolution a hundred years later would put this into overdrive, but the very idea there is enough for everyone and everyone gets a fair shot at it is born from the American Revolution. Scarcity is an Old World concept that should be left there.

Washington saw to his own material security, then helped others, seemingly including his slaves and an attempt to help the natives. He controlled what he could, as exemplified by switching his estate’s business model from a declining one to a self-sufficient one, even if his new model only gave him the status of not being indebted forever. He built his way out of problems, as evidenced by his shipyards. Washington recognized and championed creativity and discipline from his subordinates, as evidenced by Lafayette’s disregard for rank and his commission of Nathanael Greene, a planter turned general whose mastery of logistics single handedly defeated the British campaign in southern colonies. Washington could make the most of a bad situation (including ones of his own making) and escape with his reputation intact because he was pragmatic, bold, and a little bit lucky.

Washington did not end the victimization of people, nor have we. As long as we have free will, it may not even be possible. But we can work to establish thresholds of food, housing, and public health. Consider that one of Washington’s most important decisions during the Revolutionary War was to demand the Colonial army be inoculated against smallpox, giving them an enduring advantage over their British opponents whose forces and mobility were degraded due to New World diseases. Every day, we can work to get closer towards it, even if there is an event horizon beyond which he could not guess the state of the world. How would democracy spread? How should the US interact with the world after it has consolidated power? Washington never ventured a guess, not because he was indifferent but because the people of those eras would need to find their own pragmatic solutions. They would have to choose to victimize or to synthesize.

Today we face our own set of confounding questions: How will AI transform our world? Will China go to war? Will Trump dissolve the US-led global order? Will a more competent, capable, responsive federal government rise from efforts like DOGE? These are my event horizons, and all we can do is see to our own material security and work to make tomorrow better than today, putting an end to victims of history where we can.

Ultimately, Ellis answered all my questions and then some about Washington. I can see the imperious man and probably would not want him as a landlord, though given his people’s loyalty, I suspect he was a great boss. The more time I spent in that era, the more it was clear how pervasive the cultural attitudes were about power being derived from taking from others: life was zero sum. Against that pitch black background, Washington and the founding fathers still shine bright as a positive sum game—that the world does not have to be that way, that we can make it better everyday, and that such an endeavor is worth committing Our Lives, our Fortunes and our sacred Honor.

Elias shares Washington’s words from a period of immense uncertainty about the country that rings true today:

“We are either a United people, or we are not. If the former, let us, in all matters of general concern act as a nation; which have national objects to promote, and a National character to support—If we are not, let us no longer act a farce by pretending to it.” In effect, Washington believed that America’s hard-won independence would be short-lived unless the “United States” became a singular rather than a plural term, because a mere confederation of states would become, as he put it, “the dupes of some [foreign] powers and, most assuredly, the contempt of all.”

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Pat Gelsinger “retired” this week from Intel, reportedly after losing the board’s confidence. His strategy of IDM 2.0, in which Intel sought to manufacture products for itself (known as Intel Products) and for others (known as Intel Foundry), is all but dead. Commentators have wondered if Gelsinger could have done anything different in his three short years. I believe he could have, but understanding why requires some understanding of how semiconductor manufacturers are organized.

Technology development is a core function of semiconductor manufacturing. In some companies, it is literally called technology development, though it often is specified as process technology development or logic technology development. These all refer to the same job function, and unless otherwise specified, assume I am talking about whomever is doing that function inside the organization. Moore’s Law is literally built by these teams. I have not seen a good explainer of what they do and why, so I wanted to provide that as context for how they operate inside big companies. 

I strongly suspect Gelsinger failed to radically change Intel’s fortunes due to not radically changing the culture of Intel’s TD group. In fact, they may not even have the right skills inside the company to serve external customers. There is lots of evidence that he tried to change this, notably through the failed acquisition of Tower Semiconductors. I acknowledge it is possible he did fix it, given how fast Intel is churning out new nodes, but in that case it did not happen fast enough for the board’s liking, which means the board should be fired.

So we’ll start at the beginning to understand what TD is given and what they are expected to produce, how the TD team interacts with other teams in an IDM model and a foundry model, and then analyze why TD’s culture explains IDM 2.0’s struggles.

Inside Technology Development: The Heartbeat of Moore’s Law

Nodes, Transistors, and the Science of Scaling

Moore's Law is the observation that the number of transistors on an integrated circuit will double every two years with minimal rise in cost. Modern nodes take much longer and have actually increased in cost per transistor, so Moore’s Law has weakened substantially but still advances. Derived from a paper written by Gordon Moore, a key technologist in the early history of semiconductors and a founder of Intel, Moore’s observation was based on the trend of what successful semiconductor companies were delivering at the time. That trend was consistent with his own experience: Intel’s strategic planning called for Intel’s manufacturing team to deliver roughly double the number of transistors every two years at the same cost to keep their products ahead of the competition. It is what his team had to create, an organizational function known as technology development (TD): 

Marketing Inputs (Gordon Moore era): More transistors, ~every 2 years, same cost

Bringing chips to market on a new process technology requires coordination between three functions: product marketing, chip designers, and technology development. Product marketing cares about the product that gets built: what workloads get targeted, how well it performs, when it is available in volume, and the value and cost of the chip. Chip designers primarily work in the realm of circuit schematics, essentially logic blueprints for how the chip should function. They know optimal circuitry for balancing power and performance, but they need to know what the process looks like. A rough analogy is that they are architects designing houses out of materials that the technology development team creates. At the leading edge, that process is still in development, so chip designers rely on the teams developing that technology to coordinate with them on the performance, process assumptions, and design rules for that new process.

Technology development is best thought of as the front-end for silicon manufacturing. TD fundamentally must expose silicon manufacturing as software. Chip designers are the customers for TD. Chip designers specify the system spec, the architecture, the functional design of the chip, how the logic should work, and how the circuits should be connected. TD must tell them how to actually manufacture those circuits, or rather, the optimal way to place those circuits to get the best results from that process. In some ways, TD is working in reverse from the chip designer, trying to synthesize billions of dollars and decades of research of semiconductors into something that is performant, reliable, and cost-effective for chip designers.

Ann Kelleher, Intel’s outgoing head of Technology Development, said, “I view the process and technology, as the heart at Intel, because if we do our job really well, we deliver not just the present, but we’re also making the future. I tell my team that we need to deliver really well the present, but we're also making the future.” That is, TD at any semi company, including Intel, is responsible for Moore’s Law. Every silicon manufacturer must have a group responsible for TD, even if not every group calls it TD like Intel does.

TD’s core deliverable is the node. A node in semiconductor manufacturing is a collection of features that a production line can create on an integrated circuit. Each node is fundamentally transistors (switches) and interconnects (wires connecting the switches). Each node is characterized by the power it consumes, its performance i.e. how fast the switches can switch, the area or the physical size of common features, and cost. The node is the ultimate deliverable, but to access it, chip designers need it codified in software. The node will ultimately need to be packaged in a process design kit (PDK), which expresses in code the design rules for turning pure logic into transistor schematics. A PDK is a combination of process assumptions and the design rules for a given node. Process assumptions are all the physical parameters like wire resistance, wire width, line width roughness and many electrical and lithographic parameters. Design rules are established on top of process assumptions. In the VLSI design flow shown above, the PDK is the software tool that translates the desired circuit design into a physical design. The physical design is only appropriate for that specific node.

TD Output: Node(Power, performance, area, cost)

Moore’s Law fundamentally means that a new node is not the best one after about 2 years, so many aspects of each node must be updated with each new generation. Here, I’m going to drop an assertion that most people either miss or don’t fully appreciate about Moore’s Law: smaller transistors are better because they use less power to switch, can usually switch faster, and take up less space. Fully explaining this assertion would be another essay, so feel free to ask for nuance in the comments (there’s lots of it). Taking up less space means both that you can fit more in the same area and that you can create more transistors with the same number of lithography steps. Drawing smaller transistors starts with being able to draw smaller features i.e. being able to precisely hit materials with light at increasingly smaller wavelengths. Creating smaller features is primarily the field of lithography, though the entire process has been optimized. Other critical steps include deposition (placing material in layers as thin as a single atom in a precise place) and etch (removing those layers in precise locations), which allows for the bulk construction of these fine features over time. Together, these shaped the manufacturing inputs to technology development:

Manufacturing Inputs: Tools (e.g. lithography, etch, deposition), materials research

The Shape of Progress: Transistors and Trade-Offs

Drawing smaller transistors was how most of Moore’s Law worked until about 2005, a process known as Dennard scaling which advanced until it hit the thermal limit for silicon. We still draw smaller transistors, but the shape of the transistor became much more important to getting performance improvements. Those shapes are their own field of research that must be curated and edited to be suitable for a high-volume manufacturer. Until 28 nm, most transistors were planar. FinFETs were necessary to start scaling performance with Intel’s 22 nm. Now, with process nodes <5 nm, a new design is necessary, called Gate-All-Around FET or GAA. For reference, a single atom is 0.1-0.5 nm, so at ~5 nm this entire process is taking place on the scale of ~10 atoms. Electrons start behaving less predictably at this scale, and new designs are meant to make them act more predictably through careful selection of the shape and material. 

The shapes can be biased in certain ways. Changing the specific dimensions of source, gate, and drain optimizes transistors for different applications. A high-power device may be willing to consume more power if it can switch faster. A low-power device may prefer the opposite. If a node wants to offer both, it needs to determine which transistor shapes it can support in a catalog. The question for each shape is if “the juice is worth the squeeze”. New shapes introduce chances for errors. TD has an incentive to push designers towards what they know works best, though designers want to push TD towards what they believe will give them the best performance (and make TD figure out how to do this with high quality). How these conflicts are resolved is a key to understanding why IDMs make for awkward foundry partners.

Research Inputs: Transistor shapes, shape optimizations

The Wiring Problem: When Chips Are Cities

With an understanding of the minimum feature size the tooling can support and an idea of which shapes deliver optimal performance, TD can start assembling these transistors into cells. Standard cells are collections of transistors and interconnects that enable basic features. Defining standard cells and how they can route together is a core way to define a node in software. The cell structure is often defined by the cell height, minimum transistor dimensions, minimum spacing between transistors, and wire placement. Each of these decisions constrains chip designers in different ways, as they try to optimize the chip-level performance. In modern chips, signals must travel between different parts of the circuit within a clock cycle. The longer the wires (or interconnects), the more time it takes for the signal to propagate due to RC delays (resistance and capacitance effects). If a signal takes too long, it can cause timing violations, leading to errors in computation. Think of it as traffic on a highway. The farther the car has to go, the longer it takes, especially if the road gets congested. Long wires consume more power because they require more energy to drive signals across the resistance and capacitance of the wire. This is critical in low-power design (e.g. mobile devices) where battery life is a constraint. Pushing a heavy object farther requires more energy than moving it a short distance. Efficient chip design tries to minimize wire lengths to reduce delays and power consumption. However, as chips become more complex (e.g., in System on Chips (SoCs)), wire reach determines how easily different functional blocks can communicate. This leads to trade-offs between chip area, performance, and manufacturability. 

Imagine designing a city. If essential services (like hospitals or fire stations) are too far from homes, it becomes inefficient and potentially dangerous. At smaller process nodes (e.g., 5nm or below), wire reach becomes even more critical because wires don't scale in the same way as transistors. They occupy more area, contribute disproportionately to delays, and impact overall performance. If your house shrinks, but the roads don’t, it’s harder to fit everything efficiently.

Remember that nodes usually improve on previous nodes by drawing smaller features. But sometimes not all of the features can be reduced by the same amount, as it can change performance or manufacturability. As a result, sometimes features simply are removed. In SpaceX parlance, the best part is no part. However, there are tradeoffs. Fewer transistors means each transistor must be more performant to achieve equivalent performance. Alternatively, the same number of transistors would achieve higher performance.

The changes in standard cells are why any circuits designed in previous nodes will not translate to new nodes, not without porting. Porting is the process of re-mapping desired functions into the design rules for that new process node. The process carries significant development costs, as the design needs to be re-validated in silicon and any issues need troubleshooting. In the modern semiconductor manufacturing world, electronic design automation vendors (EDA) like Cadence, Synopsys, and Siemens own libraries of standard cells. The EDA vendors partner with the TD team to ensure standard cells that most designers need are available on their platform. 

The PDK is nearly complete. With the standard cell libraries, foundries provide other information necessary to appropriately place cell libraries, including the design rules on layout, spacing, and layer usage, physical layouts for placement and routing, abstracted layout information for automated routing, timing, power, and noise models, detailed circuit descriptions for analog simulation, and device models to simulate the final chip’s performance and verify it is performing as expected. 

To summarize, TD takes as inputs market requirements, manufacturing capabilities, and novel research ideas to create a node, characterized in software as a PDK. With the PDK, chip designers can effectively plan their chips.

The Culture of TD

TD has arguably the most demanding job in semiconductor manufacturing. TD has to model and predict how quantum effects at the sub-nanometer level will translate into making AI chips attain even higher model flops utilization. They must develop features on the scale of 10s of atoms that can be manufactured billions of times. TD often has to call its shot 3-7 years before a transistor ever gets produced, committing the company to fabrication processes nearing the $40B mark. If they get it right, the chip designers have access to the best, highest-performing technology before anyone else. The chip designers will pay huge prices for the wafers because they too can dominate their chip markets by being better, faster, and cheaper. If TD screws up, the chips become too expensive or too late. In the worst case, the $40B fab can literally be too expensive to turn on because of the cost of running the thousands of tools inside. Generally, when you hear of a process node being delayed, it is because something has gone wrong in TD’s purview. 

More than anyone, TD carries the responsibility for Moore’s Law. In a word, TD teams are cracked. They know it too. To get a sense of their self-esteem, consider the case of Sam Altman, CEO of OpenAI with previous experience guiding the YCombinator startup accelerator. As far as I can tell, Sam has no experience manufacturing semiconductors. Sam Altman presented a grand vision for how TSMC could spend $7 trillion to make brand new factories to power his aspirations for AI. TSMC reportedly dismissed Sam as a “podcast bro.” 

TD teams are people. Understanding how they interact with teams in different business models is critical to understanding how TD manages its responsibility to the company. 

Intel’s TD Culture: Designed for Dominance, Not Flexibility

In the IDM model where companies design, manufacture, and market their own chips, the business groups (i.e. product marketing) define what success looks like—what markets are the future? What products will win those markets? How different do they have to be vs. today? Everyone has an opinion here, and the consequences of the investments are so important that frequently the CEO is the decision maker. When critics say they want an engineer as CEO of the company, it typically means one who can synthesize where analysis says the market is going with the right technology strategy to get there i.e. what do you really believe about the markets and what is the best way for TD to address it. Operating the fabs efficiently is critical, but they can only optimize what TD has defined.

One group has not been mentioned very much: the chip designers. In Intel’s case, it is a given they would make CPUs, the only question is for which markets. CPU designers can do novel things with their architecture, implementing new circuits, adding additional cache, and adding accelerators for new kinds of workloads. Through Andy Grove’s era at Intel, desktop PCs were the dominant computing format, and CPU design was about curation. In manufacturing lore, IBM was great at developing novel kinds of transistors and circuits but it created bloated manufacturing processes that could not do anything particularly well. That era of Intel succeeded by focusing on high-performance designs that TD could manufacture in the millions. Chip design had lots of room to explore but had many constraints by TD in what they could actually produce.

This dynamic is essential to understanding how TD works in an IDM: TD can tell a chip designer “no”. TD is responsible for ensuring their product can be scaled to the millions of units with the right schedule, quality and cost. TD can, and in some cases must, be rigid to ensure the company’s success. If TD delivers something in the product group’s target, it is the chip designer’s responsibility to build the right chip out of the Legos provided. If the chip designer believes they could do a better job with different Legos, it is not TD’s problem. In the most extreme case, TD can change the PDK if they develop a better way of doing things or simply learn something is not working. Changing the PDK would set back the chip design team by ~6 months, as the development flow restarts from physical design. What is the CPU design team going to do about it? If their bonuses are tied to shipping a design in a specific quarter, what can they do but ship as soon as it is ready? Same problem for the schedule. Everyone is looking at TD, asking when it will be ready. If they say “soon”, what recourse do you have? A chip designer cannot take their business elsewhere. If TD misses their schedule and continues to put other teams behind, it destroys team trust and culture.

Similarly, the time and pressure on TD to deliver means that they will take matters into their own hands. The IDMs predated the entire EDA market—they had to build their own EDA tools and process flows. As the EDA market grew around them and standardized designs and process flows, IDMs shrugged. They saw no benefit to changing their development process to something industry standard. When they need to develop libraries, they will only pay to develop and port libraries essential to their product group. If no product would use that cell, why spend money developing or porting it?

The Foundry Advantage: Why TSMC Outpaces Intel

The foundry model has a TD team but (usually) no Product Marketing or Design team to whom they answer. As a result, they have to anticipate what the market wants and work closely with many different customers to ensure they build the right process tech. Given the costs of new fabs, foundries seek out anchor clients: a chip design company that wants to work with the foundry to set TD’s requirements, ensure the process is optimized for themselves, and get the first access to the parts. Apple is famously TSMC’s anchor client. 

The cost of being an anchor client is high in both engineering time investment and committing to buy wafers for technology that does not exist yet. While NVIDIA would love to be TSMC’s anchor client, they simply do not buy enough wafers today to do so. Would they want to be an anchor client somewhere else? It is plausible, though the alternative would have to offer comparable schedule, quality, and cost as TSMC.

Still, TSMC cannot get too enamored with their anchor client. It is important to service them first and also prepare every other customer to be successful. When TSMC began, they were not the best at anything, but they were pretty good and the only foundry in town. A fabless company had to work with them, and they had to work with fabless teams to get any revenue. If a design team showed up and asked if they could tweak a process, TSMC learned to say yes—assuming the customer will pay for it. As a result, TSMC’s TD culture is one of flexibility to customer requests. They work to say “yes”. They have to anticipate customer desires, especially in sensitive areas like changes to the PDK. As a result, TSMC developed a disciplined process of sharing PDKs with target ranges and clear guidelines about what might change and by how much. I am lacking good data, but my perception is that, at first, this was much slower than Intel’s model. However, it proved more robust over time, especially when Intel infamously struggled to get 10 nm to a production state circa 2014. At that point, TSMC had more wafer demand and a better TD team. They have never since trailed Intel in introducing the best process nodes.

By pioneering this model, though, TSMC enabled an ecosystem. In fact, the EDA vendors only really exist because TSMC enabled fabless chip design. Anyone trying to sell IP to a fabless chip designer, including the EDA vendors who maintain their own IP libraries, has to validate it in silicon, typically at their own expense. TSMC has all the best customers, so TSMC is their path to market. As a result, TSMC has the deepest, widest portfolio of tools and IP that costs TSMC nothing.

Lessons from IDM2.0’s Collapse

Pat Gelsinger left Intel this week after a spat with the board, as his strategy of IDM 2.0 went sour. IDM 2.0 was supposed to take the IDM model and add-on a foundry. They tried this before in 2015-2021, which I participated in, but Gelsinger put it as the centerpiece of his strategy. To be clear, I had no direct work with TD, I was extremely junior, and had only pleasant interactions with TD members. In truth, they were kind of my heroes. Yet, I heard the stories and saw the inherent conflicts in trying to ask TD to serve both an internal product group and the market. I see their hands all over the collapse.

To win a fabless chip designer’s business, the foundry has to answer some basic questions. The biggest question is if an IDM will try to compete with the customer. An IDM’s TD team cannot do anything but say they will not and honor it. If they ever give customers the perception that they are competing with them, the business line is over. The next question is how good is the node (again, usually defined by power, performance, area, and cost). The answer is usually “very good…if you design it the way we tell you.” Any foundry gives the same answer, but prospects will quickly find that the standard cells and IP that the IDM supports are only the ones they use. If the prospect requests something different, the answer can range anywhere from “no” to “you are stupid for wanting to do it that way” i.e. the same set of responses they might give an internal CPU designer but a far cry from what TSMC might offer. To accomodate customer requests, a foundry staffs multiple teams around the globe to address customer design questions at all hours. An IDM might staff one design team that works 8am - 5pm Pacific, because that is when their own design teams work. The final question is if the ecosystem supports the tools and processes they want to use. If they are not using the exact same thing (which they almost never are), the tools and IP would have to be ported to the new process. Someone has to pay for that, and (worse) be the first time someone tries to use it on a new node. 

The incentive structure for TD teams inside an IDM is not conducive to customer service, a core muscle that TSMC had to develop to exist. With Gelsinger’s departure and Samsung’s own semiconductor manufacturing woes, the contradictions of the IDM model servicing outside companies seem obvious. If Intel’s board decides to spin off the foundry (subject to any restrictions by the federal government to receive CHIPs Act subsidies), the TD team will have another layer of the stack to master: pleasing chip designers. An entire generation of technical talent will have to learn they are not the first and last word in semis.

The story of Intel's IDM 2.0 failure underscores a fundamental lesson: aligning technical capabilities, organizational culture, and business strategies is essential in a rapidly evolving industry. Technology Development teams hold the keys to Moore’s Law, but without adapting to external market needs and fostering a customer-centric mindset, even the best-engineered solutions can falter. As the semiconductor landscape shifts, the industry must reckon with how to balance innovation, collaboration, and agility. Intel’s struggles serve as both a cautionary tale and a call to action for companies navigating the complex interplay between legacy systems and future aspirations.

Thanks to Julius Simonelli and lithos_graphien for reviewing drafts of this work. Any errors are my own.

Since the US dropped an atomic bomb on Hiroshima, nuclear weapons have been a singular force shaping relationships between nations. The first atomic age was a race to build and stockpile nuclear weapons, with many countries choosing alliances with nuclear powers like the US in lieu of building their own. The second atomic age was characterized by disarmament because the US and USSR thought fewer weapons would reduce the chance of a civilization-ending nuclear holocaust. The USSR’s dissolution would accelerate the need for disarmament. The newly formed eastern European governments were ill-prepared to control a stockpile and were encouraged to return them to Russia or disable them. With Trump’s second electoral victory, we are entering a new atomic age: proliferation.

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US citizens’ decisions have weakened the US security guarantee. The guarantee was created to try to prevent another world war. The security guarantee states that a war against one is a war against all, requiring a response of the allies’ choosing. Americans and free Europe believed such a guarantee would deter a power-hungry authoritarian like Hitler or Stalin from conquering their neighbors. To be credible, it must include potential nuclear strikes by the US against an invading force. Though still sharing security guarantees with the US, the United Kingdom and France each developed a domestic nuclear strike capability for different reasons, though the common thread is that their quantities are intended to deter an invading force rather than to completely annihilate any aggressor nation. Only the US and USSR developed that capability. The mutual defense guarantee has been a constant of US foreign policy since World War 2, regardless of the party in power. Every new president from 1946 until 2016 endorsed the mutual defense guarantee, until Trump’s first administration refused to endorse it. Trump accused the other countries of failing to meet their defense spending obligations in order to fund their generous social services i.e. freeriding on American defense spending. This accusation put a spotlight on an open secret. Allies believed the accusation was a negotiating tactic rather than a dissolution of the security guarantee, but calling it into question added uncertainty to a policy that requires certainty to work. By electing Biden in 2020, US citizens effectively chose to endorse the security guarantee, sending a message to allies that they would not be left to fend for themselves. Since then, Trump has debated going beyond de facto withdrawal from the treaty and officially withdrawing from the alliance. With his re-election, Americans have sent the opposite message. Vacillating every four years creates a strategic ambiguity of what the US would do in a conflict. This position shifts the US from an iron-clad mutual defense of the free world to “fuck around and find out”. The ambiguity of alliances returns us to a world closer to the conditions that created World Wars I and II. A rational actor should discount the guarantee, knowing Americans might not commit to deter a war but may show up late and prevent total subjugation. There are precedents: WW I, WW II, Korea, and a disastrous attempt in Vietnam. Regardless, a rational actor should work towards securing their own countries.

If you believe these countries have an interest in nuclear weapons, the next question is if they can credibly build them. Again, North Korea has nuclear weapons, and Iran is developing them. Neither developed them from first principles; North Korea was given assistance by the USSR and Iran, sanctioned by most of the world, is presumably receiving assistance from North Korea. If these isolated countries can obtain and maintain a nuclear arsenal, most advanced countries in Europe, the Middle East, and Asia could easily follow suit. The most challenging part is obtaining fissile material e.g. uranium or plutonium. That material must be enriched with hundreds of centrifuges, which would be a trivial task for many countries with both nuclear power plants and an advanced manufacturing base. Countries like the Netherlands, Germany, Japan, and South Korea have long had the capability to build these weapons. What they have not had is a reason to fear for their security, until now. Arguably, building a domestic industrial base for nuclear weapons is easier than trying to build the industrial base required to master the kind of warfare seen in Ukraine, but I will save that for another post.

A world filled with nuclear weapons and fewer alliances is potentially safer, but I would not bet on it. Some scholars believe if everyone had nuclear weapons, no one would attempt to conquer another out of fear of a retaliatory strike, especially if the defending country felt that they were on “death ground” i.e. they had no option to surrender and live in peace, only fight or die. This equilibrium only makes sense if each country can secure a quantity of weapons to deal with any threat, which seems implausible for smaller eastern European countries trying to defend against a Russian invasion. Worse, breaking the so-called nuclear taboo by unleashing a nuclear weapon to defend oneself could invite a nuclear response that still escalates the situation, potentially outright killing everyone in the country. It may not even be by the host aggressor. For example, I worry greatly about a subjugated Ukraine, where Russia enslaves the population and forces anyone capable of holding a rifle to march into Poland to fight for Putin’s glory. With a nuclear weapon, who would Poland fire against? Ukraine or Russia? These are the fears of the Cold War, and they are returning to a more fragmented world. Nuclear weapons could simply disappear, being quietly traded between countries. Official or unofficial authorities could sell nuclear weapons for their own profit. Governments with weak institutions could fail to prevent rogue groups from taking control to use towards their own ends. The failure modes are plentiful, and the more nuclear weapons circulating, the greater the chance for a mistake. Unlike the tit-for-tat logic of the Cold War, there may not be a nuclear holocaust scenario if there is no complex web of alliances, but there are still plausible escalation paths. For example, a defender uses nuclear weapons to defend themselves. The aggressor, telling the world the defender has broken the nuclear taboo, responds with an overwhelming nuclear salvo that destroys the country—then marches into their neighbor. How should the next defender respond? 

Such nightmare situations have no good choices, only some choices that are less bad than others. The least bad option now for other countries is to hope for the best from American security guarantees but prepare for the worst. France, to their credit, has attempted to preempt any European countries building their own weapons by floating a potential nuclear security guarantee to other European countries. Yet, countries are still likely to see to their own defense as many fall outside that guarantee or do not entirely trust French promises . Since the invasion of Ukraine, these countries have increased their defense spending as a percent of GDP, some nearly doubling the spending. It seems all but a foregone conclusion they would also pursue nuclear weapons programs.

Welcome to the third nuclear age. 

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Thanks to Andrew Miller, Kevin Kohler, and Emma McAleavy for reviewing drafts of this post.

Former US president Franklin Delano Roosevelt argued that the US is defined by four freedoms: freedom of speech, freedom of worship, freedom from want, and freedom from fear. Material progress and policies focused on abundance are centrally concerned with the latter two, freedoms from want and fear. The question, then, is how do you know when enough is enough? 

In fact, the term abundance is loaded with strategic ambiguity. It is strategic in that it allows progress thinkers to rally behind one common cause, which is immensely useful. But when the systems are examined in more detail, the complexity reveals that a state of abundance may be very different between each domain. Air is abundant. Clean drinking water is abundant. In our lifetimes, text messages went from an expensive, metered resource to effectively abundant. When Boris Yeltsin visited a grocery store, he probably thought Americans had abundant food, which has  only increased in both variety and quality while still  leaving Americans wanting more. These reveal different and, in some cases, moving end-points of abundance. If we want to pursue abundance, we need to know what it is. 

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The only thing that is truly scarce for humans is time. All abundance is fundamentally about enabling humans to do what they want with the time they have. A rich person can have everything in our society, but a society could be abundant without reaching that standard. Instead, an abundant society is structurally affordable, such that any individual can provide for essentials in a minimal amount of time of their own effort.

As we push for abundance in different domains, I thought it worthwhile to be more specific about how we might achieve structural affordability because it probably won’t look the same in different dimensions and could lead to subverted expectations. My goal here is not a rigorous, academic dissection of the topic. Rather, I want a rough taxonomy for the public to understand not all abundance is going to look the same, but the point is you will not want for the essentials of life and you will have the time to pursue more. This exercise is roughly inspired by the distinctions of free beer, air, and speech, applied to the domains we take for granted (oxygen and water), the domains undergoing immense change (energy), and domains that need immense progress (housing and healthcare).

💨Abundant as in oxygen: Oxygen is naturally abundant (at this stage of Earth) and serves as my control for how to think about other kinds of abundance. When I talk about something being abundant, I think about oxygen. It has a few unique characteristics: it is elemental, free of charge, widely available, and in massive supply. It is rivalrous (the air I breathe is not air you can breathe) but it is not excludable (you can’t make me pay you to breath or at least not without causing a fight). While there are oxygen bars offering premium oxygen, on the ground of Earth the supply for oxygen dramatically outstrips the demand in pretty much all locations. While I would like for most of the other necessities of life to be like oxygen, that seems both unlikely and unnecessary to achieve abundance.

💧Abundant as in drinking water: Drinking water is only a small walk up the chain from oxygen. It’s just hydrogen and two oxygens, a molecule. The challenge is in getting only those molecules. Drinking water is in fact a private good, as it is both excludable and rivalrous. However, it is so essential to life that we declare it a human right, up to some threshold. Civilizations are built and destroyed on being able to provide sufficient hydration, such that it is in society’s interest to ensure drinking water is cheap, accessible, and ubiquitous. The abundance of clean drinking water is a great feat. Natural fresh water itself is naturally scarce. If an area had a drought, early hunter-gatherer societies would need to follow the fresh water. Refining fresh water into clean drinking water was really only possible with modernity, where prior generations preferred to drink spirits if they could afford it. Today, drinking water is not usually a natural resource, rather it is produced. It is not free of charge, but it is very cheap. Through great effort, it is widely available. When planning water uses, drinking water is prioritized, but farmers know the supply cannot always keep up with demand. Drinking water is part of a human-designed system that guarantees access at low cost to consumers with capacity and utilization constraints dictated by physics. The utilities that manage those systems have to justify their investments to both the communities that give them regulated monopolies and to the investors whose capital they have to put to productive uses. A University of Michigan study from 2022 found that “nearly one in ten households spend more than 4.5% of their annual household income on water and sewer service”. Similarly, the US government claimed that “more than two million Americans lack access to clean drinking water at home, and more than one million Americans don’t have the plumbing required to flush a toilet.” Together, these facts speak to the difficulties in engineering abundance universally even when we have the tools to do so. Could drinking water be 10x cheaper? The only plausible scenario for driving costs this low is if solar energy dramatically reduced the cost of desalination. I am not sure our life would be much different with 10x lower water costs, though it may have many benefits for the environment and agriculture.

⚡Abundant as in energy: Energy in its natural state is extremely abundant, but the abundance we care about is the kind we can actually use, when we want it, in a form compatible with our application. That too is more of a private good (or typically a service), though again the advent of electricity has made it worthwhile to provide electricity as a public utility. Regardless of how you produce energy, there is a cost to the user. Solar cells, petroleum, coal, and nuclear will always have a cost component. For a long time, the goal for energy has been “too cheap to meter” and for good reason. Energy abundance is probably the single biggest lever to lowering the cost of everything because energy is consumed recursively throughout the entire economy and many applications are limited by energy costs. It is excludable—a utility or the fuel pump can turn you away if you do not pay—and it is rivalrous in that the fuel or electrons I use are not fuel or electrons you can use. Energy for these purposes is a true commodity, where each unit of energy can be transformed into work. That said, there are meaningful differences in their generation’s impact on carbon release, the energy density of storage, the timing of energy release i.e. you may need power when there’s no solar, and the time required to replenish energy. The point, though, is that all energy can be effectively modeled as the cost to generate, cost to distribute, and the efficiency of the system. 

🏘️Abundant as in housing: To be clear, housing is not abundant in the US today; but it does not have to be this way. In circumstances with varying consumer preferences and high capital costs, abundance is about supply responding to demand. Housing is a product, a pretty big one too that has real costs in materials, machines, and labor. Housing location is exclusive; if I live in a place, I am selective about who, if anyone, can live with me. People also have strong preferences that likely shift over time: my college dorm room was fine but not OK with a wife and dog. Making housing abundant like air is a great sci-fi setting, but generally I think people are just happy if they can get what they want, where they want it, at a fair price. Just building equal numbers of all kinds of housing in one area would be inefficient for the customers and investors if there isn’t an equal distribution of demand. Notably, the USSR built lots of housing of a similar style in the interest of speed and efficiency, and it was reportedly terrible. Like Boris Yeltsin being impressed with the selection of a grocery store, we would likely find a market with deep supply across segments that can quickly respond to demand to be abundant.  Capital efficiency matters here too, though in a truly abundant society, a house may not be a great asset, at least not to build wealth. Rather, their primary role is a place to live, ideally as an asset with stable value and liquid enough to sell and relocate somewhere more desirable should the time come. Houses themselves might not be an investment, but a firm producing housing designs and the land under housing might be (something something Georgism). 

🏥Abundance as in medical care: Like housing, the end-state here is more like housing than air. An ideal outcome is getting the right care, when it is needed, at the lowest possible price. There are natural impediments to this: there is a finite supply of people suitable for serving as a doctor or nurse, the education required to provide effective medical care is intensive, and the quality of care delivered can vary significantly based on the provider, the patient, and the nature of the illness. All of that is to say, achieving abundance here is hard. But there are obvious improvements available. For one, the American Medical Association intentionally restricts the quantity of doctors admitted every year to keep prices up. Stopping cartels at least has a straightforward solution. While our goal is structural affordability, it’s worth asking if medical care could ever be “too cheap to meter”? In diagnostics, if artificial intelligence (AI) can truly deliver on its promise of expertise, AI may prove to be a path to providing at least baseline diagnostics at a fraction of the price. Most medical care is augmented by devices in both diagnosing issues and treating issues, and it is difficult to see those ever being cheap enough that they would be effectively free to use for patients. Perhaps the best outcome for actual structural affordability and patient outcomes at the population level is simply avoiding costs by not getting sick in the first place. Technology can deliver extreme helpfulness here, relegating the costs to stuff outside our control: genetic issues, infectious diseases, accidents, and afflictions like cancer that seem to be a result of simply being alive for long enough.

💊 Abundance as in pharmaceuticals: The issue that seems the most insidious is the actual price of existing pharmaceuticals. US patients are familiar with generics, the same drug carrying much lower prices because the drug’s patent protections have expired. Generics are great, as long as you don’t have to choose between living a healthy life or bankruptcy. That is the unfortunate reality of many drugs today, especially as pharmaceutical companies play games to extend their patent duration. Many countries have found a way around higher prices, by successfully negotiating for drug prices as a bloc. For example, Australians pay about $83 per month for Ozempic, while Americans pay $936 per month. One objection raised by the pharmaceutical industry about the US embracing such a tactic is that it might destroy the market. They argue the higher prices Americans pay is critical to their ability to get a return on investment such that investors will continue giving them money to operate. Let’s judge if the data supports their argument. Biopharma’s ROI stood at just 4.1% in 2023 after rising above a record low of 1.2% in 2022. For context of how low that is, highly diversified funds tracking the S&P 500 returned about 26% in 2023. (Note: I think the biopharma study is actually showing internal rate of return or IRR, which is more like 7% for the S&P 500. The point stands, biopharma as a category trails other low-risk investments.) It stands to reason that the pharmaceutical industries’ concerns about lower prices threatening their ROI have some merit. I am left with the impression that the world is actually free-riding on American healthcare dysfunction. A quick search says the US is something like 40% of the global pharmaceutical market. The US claims prices in the US are at least 2.2x more expensive than the rest of the world. Imagining a hard reset overnight, an equivalent pricing would cut the US pharmaceutical price by over half, which is all profit. If pharma R&D spending is $145B, ROI is 4.1%, then the return must be $150B. If 20% of the market evaporated, the return would now be $120B, erasing any return from the $145B investment. In a 2020 research project, The Brookings Institution came to a similar conclusion. The market would likely adjust, with either lower investment, higher prices internationally, or ideally looking for more efficient ways to develop drugs. Alternatively, the US or potentially the US and a coalition of countries could be more aggressive in pushing patents into the public domain, including novel patent buyout mechanisms like those proposed by Michael Kremer which attempts to eliminate the deadweight loss to society from patents while still rewarding companies for generating socially valuable goods.

To be clear, I would like to live in a world that achieves abundance in any of these domains more than the current  world; and I see little stopping us from achieving all of them except ourselves. Today, there is a belief at least that if you work 40 hours per week  for ~45 years, you should be able to retire (YMMV). Of course many people work much beyond that, both for very low wages (because it may be what they need to meet their life’s commitments) and very high wages (because they like what they do and are quite good at it or they just like wealth or status). In our imagined society of abundance, wouldn’t the hours required for success be much lower? It requires some optimistic assumptions about how productive human labor is across the labor pool, as we would need to generate much more value per worker in each of these fields to reach abundance, but it is a worthy goal. I imagine the pessimism for the future would change dramatically if people felt that at age 30, they had housing, healthcare, and food secured for the next 40 years. This version of the future is essentially financially independent/retire early for everyone, and while some may want to spend that time exploring or watching TV I know most would want to keep pushing themselves (I know I would). I imagine many would lead very different lives, lives somewhat detailed in the fantasies of artificial general intelligence solving all of our problems for us. Naturally, there will still be scarce resources and games people love. Status and attention (a form of time) will always be scarce, though they probably would not tolerate horrible bosses and work conditions as much. If people are healthy, happy with how they are spending their time, and feel confident about the future, I would consider it a win.

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Re-industrializing the US has been a hot topic since the pandemic. It’s certainly on top of Americans’ minds given the upcoming election. While industrial policy efforts are just starting to bear fruit, I am thinking about the ways this bet might fail. The US deindustrialized once, starting long before China’s ascent to global manufacturing superpower (manufacturing was already less than 25% of US GDP by 1990). This trend was celebrated at the time, and I suspect the root cause for deindustrialization has persisted: physical-world businesses moving atoms simply have different return profiles than digital-world businesses moving bits. Physical-world businesses have higher costs and no power law like Moore’s Law driving increasing performance and innovation.

Well into the second century since the Industrial Revolution, there are many books, articles, and case studies happy to tell future industrialists what to do and who to emulate—many of which are autobiographical and self-promoting. While Elon seems happy for others to write about him, Jack Welch was all too happy to tell you how great he was. From 1981 until 2001, Jack Welch was the icon of American manufacturing, pushing General Electric (GE) to become the most valuable company in the world. It was short lived, as the great financial crisis of 2008 exposed how his changes had hollowed out the company far more than investors had appreciated. During Welch’s era, GE would demonstrate tremendous material progress, enrich his investors and leadership team, become the envy of every other industrial company, and still set the company on a path to decline and breakup for one simple reason: financial engineering became more important than mechanical engineering. In his wake, leadership would keep his principles and strategies before gravity took hold and sent the company into decline. In April 2024, GE would split into three companies: GE would remain focused on aviation (the one, true GE), GE Vernova would focus on power generation and renewables, and GE Healthcare would focus on medical systems. In October 2024, their cumulative market cap was $316B, down over 20% from Jack Welch’s heyday. 

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What did Welch do?

For readers most familiar with modern tech companies, industrial companies like GE have many similarities. Both are fundamentally in the business of making things better, faster, and cheaper. The lifecycle for these companies is longer, though, because it takes longer for them to build factories and ship products. The factories serve as both their performance engine and a barrier for other competitors. The result is that feedback cycles are longer—it takes longer to know if a company is working well, it can be trickier to know if a company has achieved its full potential, but once decline becomes obvious, it is often very late to change things. Welch took over as CEO of GE almost 100 years into its history, found it sclerotic, and wanted to make some big changes focused on innovation, leadership, and shareholder performance, all ostensibly praiseworthy things.

1. GE under Welch delivered tremendous progress.

Welch demanded performance from his business units, and many delivered exceptional improvements to their products. GE was the first to introduce CT scanning machines, commercial MRI machines, and 4D ultrasound systems1. During Welch’s tenure, these products and others (like jet engines) increased GE’s revenue from $25 billion to $130 billion and GE’s market cap from $13 billion to over $400 billion2. In other words, GE was becoming the most valuable company in the world. 

Mini-Case Study: GE drove significant progress in jet engines during Welch’s tenure.

To illustrate this progress, let’s take a short digression into how jet engines improved over this time, courtesy of my aerospace engineer spouse3. Unlike lightbulbs, appliances, and medical devices, commoditization has not come for the jet engine. Why is that? The main customers, airlines, care deeply about fuel efficiency as it is their biggest variable operating cost. As a result, all three major commercial aircraft propulsion manufacturers (GE, Pratt Whitney, Rolls Royce) have to continually innovate to improve this critical performance metric. The market dynamics of having three competitors who are all packed with talented engineers continually embracing the latest innovations across every component has led to eight decades of compounding innovation.

Both the airline industry and the automotive industry have been focused on improving fuel efficiency over time; however, unlike cars which have been electrifying with batteries, aircraft must be as light as possible to maximize passengers and cargo. That means jet engine design is a multivariate, multi-disciplinary optimization problem: minimizing specific fuel consumption (SFC) while maximizing thrust-to-weight ratio.

The impressive compounding performance is a result of innovations across materials (e.g. composite fan blades, single-crystal nickel superalloys for the turbine blades, ceramic matrix composite turbine stator vanes, thermal barrier coatings), aerodynamic design (i.e. better modeling & simulation tools as a result of Moore’s Law), and manufacturing (e.g. 3- to 5- to 7-axis CNC machines, investment castings, additive manufacturing). Below is one such example of the compounding improvements in compressors:

The E3 was the experimental predecessor to the GE-90 core. The increased stage blade loading is a result of higher rotor speeds, lower aspect ratios, higher solidity, 3D shape optimization, and pressure ratios approaching their practical maximums for a robust surge resistant design. Similar types of compounding innovations can be seen in the combustor and the turbine. In addition to increased performance, as a flying public we all benefit from the increasing reliability (safety) and time-on-wing (lower operating expense for airlines).

What is incredible about all this progress is that it still is insufficient to explain GE’s financial outperformance and eventual downfall. A core aspect of Welchification is that the products can get better while the products become less important to the business.

2. Welch incentivized his team with options, encouraging extreme risk-taking.

Climbing to the top of Mt. Capitalism required change in GE. Both Welch’s promoters and detractors indicate that the primary transformation was GE’s new and extreme emphasis on creating shareholder value. To focus his leadership team on shareholder value, Welch famously compensated his executives with options. Today, options compensation is typical for startups but less common for publicly traded companies. Roughly, both an option and a stock give you upside exposure to the company’s valuation increasing. However, an option is much cheaper than outright buying the stock and can give higher returns for a small change in the stock price. They also are time limited, such that the option will expire and become worthless if not executed. The result for a public company like GE is a management team eager to do whatever it takes to make the stock price go up as quickly as possible. 

3. Welch was highly reactive to stock prices.

But greed alone does not tell the full story. The backdrop for industrial companies at this time was negative market sentiment for manufacturing companies, characterized by low price-to-book ratios. Essentially, other large, publicly traded manufacturing companies had a lot of depreciating assets in the form of factories that were not generating huge returns (the assets are the book part), so investors put a low price on the stock (that’s the price part). As those factories aged, the management found few investors willing to give them the investment necessary to invest in new factories, especially for factories to be built in the US. While these companies were profitable, companies with newer factories were beating them in the market. Current investors in those companies were left with the choice of letting the company reinvest their cash in the company to build new factories or asking for the money back to invest in other companies. Based on the relatively low price-to-book ratio, investors were no longer interested in backing the growth of older companies; most asked for money back.

This reputation left companies like Nabisco, Sharon Steel Corporation, and even US Steel susceptible to what is known today as a corporate raid, a usually hostile takeover bid for failing or undervalued companies by shrewd but ruthless investors seeking to extract a quick profit at the long-term expense of the company. The executives at these companies were not without blame, as they often lived large off the company’s assets (the chronicle of corporate raiding in the 80s, Barbarians at the Gates, says that Nabisco had seven corporate jets for their execs). Certainly the workers preferred their jobs to the asset sales, plant closures, and layoffs that the corporate raiders would bring. Welch saw what was happening to inefficient companies and ran in the other direction. If the tactics raiders used made shareholders happy, he would use them himself. He would only keep the best business units. He spared no sympathy for underperformance because Wall Street would spare him no sympathy. Emphasizing increasing, predictable profits and shareholder value while keeping assets low was what Wall Street wanted to see—and a driving force for deindustrialization generally.

4. Welch had no patience for industrial business units that could not deliver immediate results.

Welch had one essential mandate: GE must be #1 or #2 in a market to keep a business line. As a conglomerate, GE often found new ways to commercialize research; however, that did not mean new products were highly differentiated. Instead, many of their products, like consumer appliances and plastics, would be commoditized with time. This commodification posed a risk to the stock price. He gave several business units time to turn around, but he was not complacent to ride out market cycles. He demanded immediate strategic shifts if there was any threat to miss the expected quarterly numbers. The stock market outright hated conglomerates, slapping them with the ‘“conglomerate discount,’” which resulted in their earnings being capitalized at lower multiples than for single-business companies. 

For example, if investors wanted to give jet engines a 7x valuation of the company’s price to earnings but consumer appliances a 3x valuation, the entire company would be valued at 3x. In his first four years, Welch would divest 117 different units representing 20% of GE’s assets4.  In his first five years, he cut headcount by 25%, impacting 100,000 jobs. The company would shrink in headcount until 1994, down 45% from the start of his tenure, shedding 182,000 mostly US-based jobs. The full fate of these companies is not known; presumably, some were acquired for their patents and others for their factories. In at least one circumstance, the company’s products have survived. Malcolm Gladwell alludes to one company, GE Central Air Conditioning and Heating, being sold off to Trane, who still manufactures some air conditioning components in the US. While it is reassuring that survival and success is possible outside GE, few seem to have survived.

5. To drive market-leading returns, Welch put financial engineering ahead of mechanical engineering.

GE had been and would continue to be an innovation-focused company that intended to research and develop technologies, especially in materials science. However, those returns were insufficient to distinguish GE to investors. Welch sought capital-light businesses to augment the profits of his hardware lineup5. Welch leaned into services and financialization: extending credit to customers to earn interest on their purchases. It was a new way to monetize their existing customer base that did not require additional capital. “And you don’t have to build a factory,” as Welch said. In the same spirit, GE would become an early entrant in “software in a box” through the predictive maintenance software, a complement to their existing industrial equipment that they only had to build once and could sell to their current customers. In 1980, products represented 85% of GE’s revenue; by 2000, services represented 70%. 

GE was truly transformed. They were no longer a company making life better in people’s homes and work. Under Welch, they existed to make the number (profits) go up, even if it meant borrowing from the future. GE became a financial services giant, with internal incentives that put financial engineering before mechanical engineering. Building a new factory was effectively betting your career, a move that only made sense if the competition was going to kick you out of the top 2. This new strategy still pushed progress forward in meaningful ways, thrilled investors, and sustained for over 20 years. It would continue to serve GE for 7 years after Welch’s retirement, a kind of “coyote time” where Wile E. Coyote has gone over the edge of the cliff. In 2008, the company faced an existential threat from the financial crisis that simultaneously crushed the lending market, re-priced bad debt GE had issued, froze credit markets that GE relied on for liquidity of their operations, and reduced demand for industrial products. GE’s stock would fall over 40%. The company would continue to contract until it finally broke apart in 2024. GE’s rebirth was only a reprieve, the hour was much later than they believed, and there was no more future to borrow against.

Defining Welchification and How to Avoid It

Welchification is the strategy of deprioritizing physical world progress in the face of declining returns on those assets. Financial products that make technology easier to buy and software that improves the usefulness of machines are incredibly important to making industrial technology successful—companies need those profits to be able to continue driving material progress—but when such products represent 70% of a company’s revenue, something has gone seriously wrong. 

Welchification puts profits before any logical connections in the business i.e. a lack of focus. At some point, all material progress is limited by physics. When that happens, how do you find new growth? GE got real weird with it, making jet engines but also buying NBC (which gave us 30 Rock so I can’t complain too much). In contrast, car companies like Tesla look to move into new vehicle styles at different prices before shifting to new, tech-powered business models like robotaxis. While their ability to execute on this vision is in question, at least there is a logical progression from one technology to the next. Apple looks for new paradigms of personal computing, from your pocket to your wrist, ears, and eyes. These progressions build on one another, taking a technology for an application space to maturity then finding a new wave to follow. It helps that these are companies with a digital component that can follow wherever Moore’s Law takes them. Analog businesses like housewares have no power law driving their improvement, save for the manufacturing plant. Reindustrializing must embrace the power laws that they have.

Welchification prioritizes investments that deliver high-certainty results over the lower-certainty results later that might deliver bigger profits. Jeff Bezos, founder, executive chairman, and former CEO and president of Amazon, alluded to this problem in his original 1997 Annual Report: “We believe that a fundamental measure of our success will be the shareholder value we create over the long term.” Every year until his retirement as CEO, he revisited this thread and linked his original paper. In 2016, he wrote about what Day 2 looks like: “Day 2 is stasis. Followed by irrelevance. Followed by excruciating, painful decline. Followed by death. And that is why it is always Day 1. To be sure, this kind of decline would happen in extreme slow motion. An established company might harvest Day 2 for decades, but the final result would still come.” Post break-up, all three of the different GE business units have demonstrated growth and increased their market cap, in large part because they each only have one future to focus on and invest in.

To avoid Welchification, leadership needs to find new ways to drive progress in their product, operations, and manufacturing. Leadership needs to align their internal incentives with long-term shareholder value creation, such that teams can chase bigger opportunities without career-ending risk for experiments that do not work. Leadership must have a vision for why their products need to exist, then invest in it with conviction. The best founder-led companies do this today, often taking a short-term beating, but are rewarded long-term if their vision is right. The market will reward growth stories and focus, and the vision will energize teams through difficult periods. Leaders also need to be able to justify building new factories, ideally using their existing cash flow. They will still have to convince investors that they offer the best return on invested capital, and the best way to do that is with durable, growing free cash flow from prior investments. Industrial subsidy makes new factories easier to justify, but it is difficult to believe the US would provide subsidies indefinitely. At some point, these companies must be able to stand on their own. Rather than seeing factories as a weight around their neck, leaders need to see them as the product itself, a digital platform for driving innovation. A few key performance indicators if a US factory is an innovation driver are their ratio of robots to humans and their labor productivity (revenue per employee). In a country with relatively high wages, these measurements are critical to assessing if the company can produce sufficient goods and revenues for their investment. Ultimately, avoiding Welchification requires investing company capital to deliver long-term value for shareholders. Company leaders have to be looking at what it takes to make great products and developing the factories that make that possible. Amazon’s culture is a good model: a lean culture that constantly experiments, assesses effectiveness, and bets boldly when it sees an opportunity to win. 

Investors should reward leadership teams that know how to wield their factories as competitive differentiators. It is a strategy that works,as evidenced by the valuations for Tesla, SpaceX, and now Anduril. Policy makers and citizens must expect some of these experiments to fail, but they should also expect new ones to rise in their place. 

And if every company keeps coming to the same conclusion that building in the US is an unproductive use of capital, policymakers will need to partner with companies to better balance policy goals with material growth. Getting this right will deliver better products, profits, and material progress that, in Jason Crawford’s words, “moves us up the hierarchy of values, freeing up time, money, and energy spent on the basics and letting us redistribute them towards the fulfillment of a richer life.”

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Thanks to Rob Tracinski, Shreeda Segan, Lauren Gilbert, and Jeff Fong for reviewing drafts of this post.

The first wave of blame fell on the hoarders. When the pandemic-related shortages started, it was obvious individuals were looking to profit. The longer the shortages happened, though, the more a creeping realization slipped in. Americans knew their stuff came from elsewhere, but only then did they realize how fragile that relationship can be. 

For over a century, it had been obvious that economic theory that favored trade would make people’s lives better because it did dramatically improve most people’s lives. By 2020, there was a growing bipartisan consensus that the theory was incomplete. It never could have anticipated China, who was fast to dominate new industries and slow to embrace any sort of liberal reforms. To chart a path forward that reconciles the benefits of trade while recognizing the risks, let us revisit those theories and their assumptions.

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There are two core theories of interest: comparative advantage and competitive advantage. 

Comparative advantage is concerned with cost: does one firm have a cost advantage to make the same kind of thing? The theory has been revised several times, first focusing on relative labor costs but in modern times it focuses more on opportunity cost. I am not an economist, so I will do my best to summarize. In theory, a business will make more of a good which is relatively cheap for them to produce than another, because it represents a lower opportunity cost. The other goods can be obtained via trade. 

Competitive advantage is concerned with overall performance: what business structure will maximize profits? In contrast to comparative advantage’s focus on the cost of similar goods, competitive advantage is all-encompassing, asking how to use every part of a company’s operation to outperform others, from research consortiums to design to distribution. 

By 1990, US business executives and investors believed that manufacturing in the US represented a huge opportunity cost for their capital. Labor was much higher, and many regions had enacted strict regulations around what kind of manufacturing plants could be built there and how they could be run. Manufacturing was only 22.9% of US gross domestic product (GDP). Michael Porter would translate this competition from firms to nation-state in his essay and book, Competitive Advantage of Nations. He claims, “A nation’s competitiveness depends on the capacity of its industry to innovate and upgrade.” He puts this in contrast to prevailing wisdom, that “labor costs, interest rates, exchange rates, and economies of scale are the most potent determinants of competitiveness.” He emphasizes the dynamic nature of international competitiveness that must be earned “not just once, but continuously”. 

Yet the US abandoned trying to compete in all but the most advanced manufacturing industries like semiconductors, medical technology, and commercial airplanes. In a phenomenon dubbed the Smile Curve, manufacturing was considered to be the lowest value added activity compared to research, design, and marketing.  This theory formalized a process that started in the 1970s in the US and concluded by 2010: the US will do R&D, the US will market their products, and the rest of the world can manufacture it. As a matter of course, the US expected that most basic manufacturing is interchangeable and competitive, such that US firms could find a supplier that would meet their schedule, quality, and cost needs. Every competitor had similar machines and materials, so the only advantage was in labor rate. As a result, manufacturing fled to countries with low labor costs and friendly attitudes towards manufacturing, starting with Mexico, Canada, and Japan. But China’s entrance was unique.

Per this story in the Wall Street Journal, after Mexico joined NAFTA, it took 12 years to double their imports as a percentage of US economic output. It took Japan just as long after they became a major US supplier in 1974. In a phenomenon dubbed the China Shock, China doubled their imports in just 4 years, precipitating the end of many US manufacturers. Those manufacturers found their customer base evaporating, who were drawn by China’s similar quality and dramatically lower prices. This sudden drop in revenue cut the timeline and resources available for US manufacturers to reinvent themselves. Chinese manufacturers were able to scale their exports so quickly thanks to massive incentives for regional governments to welcome manufacturing (what economists call foreign direct investment or FDI), lax environmental policies, and the allure for multinational manufacturers to increase their revenues by accessing the domestic Chinese market. China had a massive population, eager for the wages manufacturers could offer, and China accelerated that workforce’s development with more education. In return, the government demanded that foreign manufacturers share their technology via joint ventures. Foreign manufacturers found this a fair bargain, in many cases believing China would get the technology anyway, so they may as well make some money off it. As a result, from 1990 to 1994, China’s FDI grew from 1% of GDP to over 5% of GDP. 

Over the next two decades, China would become home to the deepest pool of skilled manufacturing labor and effectively transition from being a low cost supplier to the best possible supplier for producing at scale. Americans benefited from cheaper goods, stock market returns from companies growing revenues in China, and nearly on-demand access to the latest, hottest technologies like new smartphone, TV, and laptop models. The relationship appeared completely mutually beneficial.

The economic theory took for granted the trust between two nations. In this case, the nations were organized extremely differently: the US, a democratic republic that operates on the timescale of elections, and China, a one-party, authoritarian nation. The absolute control of the Chinese economy was critical to fueling their ambition, putting total control of multiple industries in effectively one person’s hands. This structure is a known industrial end-point: a monopolizing trust. A trust’s playbook is straightforward: get the best technology by whatever means necessary, then scale output dramatically with low prices (below cost if you must) to drive competitors to forfeit or sell to you. When you are the only player left, raise profits and dictate the terms to everyone depending on you. Presently, there are fears China is pushing to monopolize more industries, as steel supply, solar supply, and EV supply are all far above demand. There are other plausible explanations than an attempt to destroy competitors: Chinese suppliers are incentivized by the state to keep producing, plausibly because their economy needs as much help as it can get. But regardless of motivation, the effect of their actions is to risk bankrupting competitors outside China lacking their government’s financial support. Those competitors are the best defense against China’s monopoly, though by now the range of goods they can address has narrowed substantially. The US has atrophied the muscles of building basic goods. Without those skills, it is more difficult to sustain a labor supply that can make the more advanced products that are important both economically and militarily. For example, chip manufacturers have experienced a shortage of skilled construction labor, and the US Navy has urgently run ad campaigns for workers to make new submarines.

These economic fears are compounded by national security fears. The most plausible fear is withholding: in a crisis, China would withhold critical goods necessary for the US to function. The other kind of fear is using their position as a supplier to stage a direct attack. This unique kind of fear was highlighted by the recent pager attack in Lebanon, when thousands of members of Hezbollah were wounded and killed as their pagers exploded after decades of terror attacks and outright war against Israel, serving as a worst-case example of a complete breakdown in trust and weaponizing the supply chain. That was with a relatively simple device, allegedly stuffed full of explosives. What more could be done if an entire network of drones or Chinese EVs were remotely controlled? Even without explosives planted, EVs are effectively a smartphone on wheels, with GPS, connectivity, and camera data that would be highly valuable for controlling and coercing a rival. The US is already racked with fears of surveillance from TikTok, who is legally obligated to share the information they access with the Chinese government. As China’s technical prowess grows, their products stoke more fear and face more threats of bans from the strained trust. These bans have precedent: networking equipment provided by Chinese manufacturers Huawei and ZTE were effectively banned because the manufacturers could not credibly demonstrate their trustworthiness and independence from the Chinese government. Continuing this trend, in September 2024 the White House proposed a ban on connected Chinese automotive components. 

Re-industrializing the US requires a new economic theory that acknowledges and addresses these concerns. It must begin with a choice, the same choice Porter put forward in 1990: nations and their suppliers must choose to compete. Choosing to compete requires a change in thinking: manufacturing is not a low value activity to be outsourced but a dimension of competition to be improved and upgraded. That dictum holds true for both simple products and advanced manufacturing. 

For basic goods, the only path for the US to build a durable comparative advantage is to build the most productive manufacturing ecosystem in the world given our higher labor costs, a good thing for a wealthy country. That means investing in our own highly skilled labor pool and augmenting it with the best manufacturing equipment in the world. This particular moment is a good one for investing deeply into productivity, as machine learning is powering impressive breakthroughs in image recognition for quality control, robotics, and other new kinds of automation. Similarly, the products the US manufactures must be internationally competitive. If what China is doing is actually selling below cost to drive out competitors, local manufacturers must find unique sources of profit to maintain their operations to sustain themselves until such a strategy becomes untenable. 

For example, in the automotive realm, that means US truck sales are actually an effective hedge on Chinese monopoly. But EVs are the growth category in automotive, and China is building the world’s best EVs. Again, the US must choose to compete and hold themselves to the highest standard. The bar has been set, and American companies must meet or exceed that bar. The best way to do that is to let the consumer choose, and simply banning competition makes that impossible. Consumers outside the US will have a choice, though, which maintains some market dynamics. In 2023, 40% of Ford’s revenue came from outside the US, which is a strong incentive to compete. 

If it is a severe national security threat, a ban is justified. A sufficiently high tariff may achieve the same effect as a ban, but why allow the threat at all with a tariff? A tariff is meant to protect local industry by making the imported product’s value proposition worse and generate tax revenue for the importing revenue. Neither of these addresses the actual problems: stopping a national security threat and making globally competitive products. A better solution would allow for a true market dynamic in the US by creating conditions that can mitigate the national security threats. Those solutions might include requiring American suppliers and data regulations that protect US consumers and national security. With the national security threat addressed, the next concern is that local manufacturing would be overwhelmed as other industries were in the first China shock. The best solution would enable them to move faster than China, a far cry from the status quo. If US manufacturers have four years to respond instead of 12 years, how expensive is a year of permitting review? (Note that projects using federal funds require a NEPA review, which averages 4.5 years.) Speed is essential to giving US manufacturing a fighting chance.

While that ideal solution may not be reachable, other options may facilitate competition while restricting China’s ability to overwhelm domestic manufacturers. One option borrows from China’s own restrictions on Western movies: limit the number of new models allowed to be sold. Eligibility could be restricted to prices that domestic manufacturers cannot or will not target to minimize the harm to consumers. For example, US manufacturers essentially do not have cars for under $20,000, so Chinese EVs priced under $20,000 would be eligible for sale. Similarly, supply limits could be put in place restricting sales. Consumers would bear the deadweight loss of restricted supply, but it would be less painful than the total deadweight loss of bans and extreme tariffs. Ultimately, there is no substitute for actual competition or moving quickly; the US desperately needs both. Wringing the cost out of their supply chain, moving quickly, and betting on machine innovation gives the US the best possible chance to compete and tip comparable advantage of even basic goods back in our favor.

By choosing to compete, seeing manufacturing as a source of competitive advantage, holding ourselves to the highest standards, and building a regulatory environment that mitigates security threats, the US economy can grow sustainably, recognize the benefits of international trade without fully protectionist measures, and have sufficient resilience to never face the pandemic-induced shortages again.

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Thanks to Rob Tracinski, Emma McAleavy, Rosie Campbell, and Sean Fleming for help with this post.

The Wright Brothers did not need a permit to fly. Ford had an extremely basic permitting process to create the modern manufacturing line for automobiles. Western Union built the original telegraph network with a permitting system largely consisting of obtaining a franchise and right-of-way, which came largely from following the railways which streamlined negotiations with local municipalities.

Most material American progress occurred with limited friction, certain that projects could move forward in a predictable, fair way. Too much friction is actively strangling progress.

Unfortunately, friction is now everywhere, across all American industries. One recent case occurred as the US frantically builds semiconductor chip fabs. Completing these projects is considered a matter of national security and so important both political parties agreed to subsidize it. The fabs could be built faster if they could forgo an environmental review stipulated by the National Environmental Protection Act (NEPA). The party typically against environmental review argued that, if everything else has to go through with this, this politically sensitive project should too, presumably to highlight the pain of permitting. If a project with bipartisan consensus on its importance to national security cannot escape friction, what chance do other industries have?

But the friction doesn’t stop at chips. Ben Reinhardt maintains a list that covers a wide range of examples. Within each industry, there are direct and indirect sources of friction. The direct sources include actual permits and regulations required by the federal and state government, such as environmental reviews, building permits, and air permits. These permits are not as simple as filling out a form and getting an instant yes or no. They take time. South Carolina has a blog post explaining their own typical duration to grant environmental permits and what factors influence their response time. Permits that only require local review range from 8-38 days. Permits requiring Environmental Protection Agency review and public notice periods start at 75 days and extend over a year to 412 days.

Indirect sources of friction would include things like roads, powerlines, waste management, water rights, and community attitudes. If they do not already exist, a new business must engage in a negotiation with the government at various levels. While most businesses do not encounter corruption, a significant amount of corruption happens through these negotiations because the government wields extensive power here, including the ability to indefinitely stall projects. Francis Fukuyama labeled the status quo as a vetocracy, a system of infinite interrupts that literally prevents progress without community agreement close to consensus.

As a result, building new industrial plants in the US requires significant conviction and buy-in from the various levels of government before committing financing. One cannot just build a new factory in compliance with the law, you need a personal relationship with the powers that be in order to operate your business. Little wonder why so much of American life feels politicized, because it is. 

Progress in advanced industries like supersonic flight and nuclear reactors is simply barred. Congress passed a law banning supersonic flight over land, and the Nuclear Regulatory Commission approved ~2 new plants since the 1970s, a de facto ban on nuclear energy as a technology. Of course, researchers push forward on paper and attempt new designs overseas, but actually building things is a muscle that must be built with practice. When industry cannot attempt new things, they cannot learn and optimize the process, a phenomenon known as experience curve effects. This atrophy is visible in areas of national security, both defense production and semiconductor fabs. It is just the tip of the iceberg. The invisible parts are all the costs added to basic kinds of manufacturing in the US for everything from cardboard boxes to data centers. Even worse are all the projects that never make it past the drawing board because the costs and risks don’t calculate out. It is impossible to find that number, and the best evidence is simply how much manufacturing for the US is done internationally. 

But it doesn’t have to be this way. To understand how to evolve, we first need to understand that friction exists for a reason.

The present system is a response to two big forces. First, powerful government officials like Robert Moses in New York City affected dramatic, controversial change in communities against their wishes. Second, industrial companies in the US caused significant harm to the environment, in some cases through indifference and others through ignorance (with big questions about what they knew and when). As a result, the modern system has little cost to halt development of any project for almost any reason as long as it is couched in environmental terms. These interruptions have an outsized effect on the interrupted, as it erases certainty of scheduling construction, making it take longer to make money, and increases costs to address legal challenges and costs of financing the project. Returning to the CHIPs Act, even now, the Sierra Club is mulling a challenge to stop new fab projects via an environmental review challenge. 

A better process would synthesize these challenges into a system more conducive to growth.

Specific to the problems discussed, companies can and should bear costs for environmental damage. Previously, the US government successfully addressed worker’s safety by simply setting default liability for companies when workers were hurt on the job, including predetermined penalties. Why not build a similar system for damage to the environment? Companies respond forcefully when these externalities are imposed on them, as demonstrated by workers compensation.

Additionally, it seems impossible to move forward without improvements to state capacity. To be clear, state capacity is not about the size of government but the effectiveness of government. To start, state governments can implement legal frameworks that guarantee projects can move forward upon certification, likely a form of ministerial approval. Noah Smith explains ministerial approval as: “...you have a bunch of government workers examine the project and make sure it checks all the relevant regulatory boxes, and then if it does, you simply allow the project to go ahead, without lawsuits or multi-year studies.” You might be mistaken for thinking that is how it works today because it is eminently reasonable and, in fact, (again quoting Smith) “how Japan does things, which is why they’ve been able to build enough housing to keep rent affordable.” States could also add a service level agreement, a common feature in services businesses where the operation providing the service is required to fulfill their duties in a set amount of time. That typically carries penalties if they do not uphold their end of the deal. The states can and should compete to develop the best system. That system is in its infancy today, with states like Texas, Arizona, and Ohio actively competing for all kinds of manufacturing projects, especially semiconductors and clean energy projects.

There are almost certainly other kinds of federal, state, and municipal reforms possible to build a culture that allows material progress. The benefits of doing so are hard to understate. For one, erasing the cost and uncertainty of manufacturing projects will make more kinds of projects possible. Ideally, industrial companies would select to build in the US because it is the most globally competitive place to build, not because of subsidization. Two, the more we build, the better we will get at it. Three, these ecosystems can create positive feedback loops, with new kinds of companies and innovations possible, as seen in older hubs like Detroit and newer hubs like Shenzhen. 

But more fundamentally, the vetocracy is an affront to a culture that values liberty and innovation. Even now, great policy wonks are at the vanguard leading the way, but they need both receptive ears in Congress and people to champion the cause in their own communities. Policy matters, but great policy is only possible with a great culture. Recognizing these issues and resolving them requires the US evolving, politically and culturally, and that must start with us. The community itself has to be pro-growth, it needs to set the agenda and find solutions that empower growth and protect the community better than the stasis produced by the expense and uncertainty of current processes. The problems are entirely of our own making, which means we have everything we need to fix them—if we have the will to do it.

Thanks to Rob Tracinski, Sarah Constantin, and Shreeda Segan for help with this post.

The US is out of touch with manufacturing, and it is obvious to anyone involved in production. When a reasonably smart person who understands technology walks into a production setting, they often lack a key skill: how to talk about production. 

For businesses involved in manufacturing, production is where they have the most control. That control must be wielded rigorously from conception. The details matter, quantification matters, and even the risks that cannot be quantified must be discussed. If the US is to build things again, better, faster, and cheaper than the world has ever seen, we must be a culture steeped in the language of manufacturing: cost accounting.

Cost accounting is not like accounting for your taxes: it is not about the past. Rather, cost accounting is a rigorous model of the future. When you understand the shape of cost accounting, you can ask the questions that let you see around corners to spot dead-ends, frauds, and better tomorrows. The fate of entire companies has pivoted on cost accounting: Intel famously told Steve Jobs they would not build the chip in the iPhone based on a cost model. That fateful decision led to them making essentially no revenue from smartphones ever. 

This is not a textbook on cost accounting, but a primer. Cost accounting is one of the pillars of understanding how and why material progress happens. It is easy to pick up and generalizes across manufacturing.

The Shape of Cost Accounting

In Andy Grove’s High Output Management, he explains the essence of manufacturing through the lens of the Breakfast Factory:

To understand the principles of production, imagine that you’re a waiter, which I was while I went to college, and that your task is to serve a breakfast consisting of a three-minute soft-boiled egg, buttered toast, and coffee. Your job is to prepare and deliver the three items simultaneously, each of them fresh and hot. The task here encompasses the basic requirements of production. These are to build and deliver products in response to the demands of the customer at a scheduled delivery time, at an acceptable quality level, and at the lowest possible cost.

Let’s revisit the Breakfast Factory, starting with a brief overview through schedule and quality before we get to cost. If you have ever sat like an idiot without food while everyone else had theirs, you understand the importance of getting the schedule right. However, if you have ever had to cook a large meal for a holiday, you understand the challenge and planning required to execute to a tight schedule.

Quality, as defined by the timeless words of Toyota, means meets spec. It does what it is supposed to do. Quality is not free. Perfect eggs require control of cooking temperature and time. In all forms of manufacturing, tight tolerances, specific shapes, or exotic materials can restrict the suitable kinds of fabrication processes, generally because they have lower throughput.

Conceptually, every manufacturing line can be reduced to two types of costs: direct and indirect. For the math inclined:

Costs = Direct costs + Indirect costs

Each of these kinds of costs can also be split into fixed and variable. Fixed costs you pay regardless of production level, like the lease on the restaurant. Variable costs scale with the level of production, like buying more eggs to serve more customers.

Direct costs can be directly traced to the product. At the Breakfast Factory, direct costs include the people who make the food as well as the eggs, coffee, butter, bread, and the coffee maker and other tools used specifically for making food. The indirect costs cannot be directly traced to the product. At the Breakfast Factory, that could include electricity, natural gas, a refrigerator, air conditioning, electronic security, cleaning materials, and waste disposal.  Each of these costs has their own progress curve that can be measured. Let’s step through each kind of direct cost and indirect cost, before pulling back to the high level view of thinking about costs.

The first kind of direct cost is labor, the cost of people involved directly in making the food. Labor rate usually scales with time, because you pay people for their time. Labor rate is the amount paid per hour to the people making the food. To get actual labor costs, multiply by the number of workers and the hours worked: 

Labor Costs = Labor rate x number of workers x hours worked / number of good units produced

In this case, we want to know how much each unit costs, so we divide by the number of good units produced. We specify good units because we do not want to be in the business of delivering food that was dropped on the floor. Be careful to include all of the labor associated costs, typically the wage plus any benefits. The wage is typically tied to supply and demand at different skill levels. You could imagine in our Breakfast Factory where the lowest skilled and lowest wage workers watch the machine make soft-boiled eggs while a higher-paid chef makes perfect omelets by hand. Progress frequently takes the shape of helping lower-skilled employees perform tasks of higher complexity. If we decided to expand our offerings from just soft boiled eggs to eggs over easy, a hand-held tool that helps workers flip eggs perfectly every time would make it easier to find staff for that task without requiring extra training. To go high-tech for a moment, some of the early studies of the impact of AI on office workers have reported similar effects.

Material is not much more complex. It is the cost of the eggs, butter, toast, water, and coffee. For each product the cost would look something like:

Material Costs = (Cost of materials used in good units and scrap) / Number of good units

How much we pay could be a function of how picky we are about the quality of each. We might pay more for a supplier we trust to deliver good products on time. The waste itself is important to track. Food can be overcooked or dropped, and food can be sent back if there was a miscommunication about the order. Both of these result in waste. The cost of waste must be factored into the cost of the units you actually sell. Here, progress looks like minimizing waste, reducing the cost of inspections, and having short, responsive supply lines. That is operational progress, which is useful, but the biggest impact often comes from material progress. Imagine a wonder egg that always tastes amazing, always cooks perfectly, and never spoils. How much would you pay for the wonder egg versus a normal egg? The cost model is essential to understanding the impact of bringing that innovation into production.

Machine rate is deceptively complex. Again, the simple version is:

Machine costs = Machine rate x hours used / number of good units produced

The machines themselves are easy to pick out: the boiler, the toaster, the coffee machine, and the pots and pans used to prepare the food. The kinds of machines we buy are tied to the schedule: how much will we need, by when? If everything has to go out together, it doesn’t make sense to spend a lot of money on a toaster that can toast in 10 seconds while you’re still waiting for the eggs to finish. We have to find an efficient solution for throughput and cost, and that is very hard. A huge part of progress in material goods is figuring out how to solve this problem with better technology and processes. So we use benchmarks and assumptions to model the cost of the machine's useful life.

For example, imagine the toaster saw constant usage for 4 hours during breakfast this morning. If it can only last for 4000 hours of use, we have consumed 0.1% of the value of the machine. We can expect to have to buy a new one in 1000 days. In some cases, a machine’s useful life is best matched to a per-unit basis; in others, its useful life is better aligned to the duration of use. The answer lies with whichever better matches to the actual cost incurred.

Machines are classically where progress happens. Progress here could mean all kinds of different optimization points. A high-pressure boiler could cook eggs faster. A bigger toaster might fit ten slices at once (i.e. batch production) more efficiently. A new kind of toaster could toast faster and more consistently. All of these machines could be integrated into one machine that does everything at the touch of a button. Machine innovation is a key path to abundance.

To summarize our direct costs:

Direct costs = Labor cost + material cost + machine cost

Progress is most visible in direct costs. Producing more with less labor at higher quality is essentially the history of the industrial revolution. But even this belies the revolutions in indirect costs, such as adding electricity, refrigeration, and air conditioning to buildings and vehicles. Forklifts and security cameras completely change the productivity of each task. Indeed, these kinds of innovations in indirect costs can enable entirely new kinds of factories to be built. Adding solar and a battery to the Breakfast Factory may get us all the power we need during the day for our few hours of breakfast production (and maybe that pushes us to consider a fully electric boiler instead of a gas boiler). 

Total costs = Direct costs + Some part of indirect costs

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There is much more that could be said about cost accounting, as it is truly the lingua franca of production. This framework generalizes to every piece of production in the modern age. Building a 50,000 lbs press to fabricate monolithic parts is better than fabricating multiple parts and assembling them (a per-part comparison requiring analysis across several lines). Conversely, cost accounting can tell you it’s better (likely for quality, throughput, and cost) to assemble a rocket out of components fabricated in multiple ways than attempting to fabricate the rocket as a monolithic, 3D printed device.

 If the US is to make a future abundant with food, energy, water, housing, pharmaceuticals, it will have to re-industrialize with sound policy and investments. Those decisions will be spoken in the tongue of cost accounting, transcribed in the tomes of spreadsheets, garishly copied into slides. 

Thanks to Rob Tracinski and Mary Hui for help with this post.

I am excited to be dedicating some time to a personal passion of mine: progress. After doing some writing on semis and manufacturing, I accepted a fellowship with the Roots of Progress Institute.

Why progress?

My life is haunted by this chart. In many ways, we live in an age of unparalleled progress. The inventions that brought us the Information Age were unfathomable a hundred years before, and everyday there are new innovations only possible with access to that much information. Moore’s Law marches on.

But few Americans feel like things are better than ever. The cost of essentials, housing, healthcare, and education, is increasingly constraining the quality of life for my generation and younger. My conviction is that reducing the cost of living while maintaining or improving the quality of life will have numerous benefits. The Housing Theory of Everything details how housing alone shapes much of modern life. I want to add two wrinkles: certainty and stress. I am certain I will need housing and healthcare in the future. I am pretty certain housing will be expensive to unattainable, depending on nearness to other people and career opportunities. I am certain my health will decline at some point, though I am uncertain when. I am certain my family’s health will be in jeopardy at some point and they will need my help. I am certain when these things happen, it will be expensive in time, energy, and cash. I can keep going: kids, education, layoffs, pets, “once-in-a-lifetime” events that have become a staple of modern life. 

These are normal stresses in life that get amplified when costs for essentials are high. Fixing that chart is the calling of our age. Fixing it will require more stuff, better, faster, and cheaper than how it is done today, starting with housing, healthcare, and education. The good news and the bad news is that it is largely a result of choices. We can change our mind and fix things.

We are not the only players on the board either. Humanity has thrived with the long peace powered by global markets, education, and American military hegemony (be nice to your local DoE weapons scientist). As Americans question their own stability and feel overwhelmed by its stress, authoritarians feel empowered. Authoritarians look to dominate those that would challenge them or simply those that have something they want. Simply, the free people of the world are under pressure to deliver. If I can help, I will. 

What are you going to write about?

My interest is in material progress: how do we build stuff better, faster, and cheaper? The next four essays will be meditations on progress as a verb, exploring some of the cultural divides between industry and the public and some of the biggest strategic questions facing material progress here at home. My goal is to contribute towards a culture of progress in America that will deliver that happy future.

Are you writing for a living now?

I expect to keep building things to make my living. This blog is propaganda for the world I want to live in and my understanding of what it will take to get there.

Are you an intellectual now?

I do not think of myself that way. I have met a few of the other fellows, and they are brilliant PhDs, researchers, and journalists much better suited to that title. I started this blog because it forced me to organize my own thoughts, and others found my perspective unique and helpful. I expect to continue in that spirit.

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How can I support you?

First, be optimistic about the future. Not in a pollyanna-ish, everything-will-work-itself-out way. It will be OK because we’re going to make it OK.

Second, make it OK. Take progress seriously. We have amazing, straightforward solutions to problems: just look at what we did for textbooks in the chart. For another example of what I mean, check out Ramez Naam on climate change. Solving the US’ issues will not happen overnight, it will not happen without effort, but you will be amazed at how good things can be with the right choices.

Lastly, sign up! I am writing at roblh.substack.com for now, after a slight rebrand to Happy Future Blog, as nobody can spell my last name but they might remember it translates from French as The Happy .

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Previously: Facing Reality, Technoeconomic Pillars of Foundry, How to Grade the CHIPs Act

As laid out in the last post, the problems facing US semiconductors are:

1. Leading Edge Problems

   1. Will the application of funds create the most advanced fab in the world?

   2. Will the application of funds make the United States the most desirable place in the world to build future leading-edge fabs?

   3. Given the goal of building more capacity at a level beyond what China is believed to be capable of, how much capacity will be generated with the application of funds?

   4. How will inducing supply affect its relationship with demand? How much risk is there of underutilization, accounting for the subsidy reducing costs?

2. Lagging Edge Problems

   1. How much will the application of funds encourage domestic semiconductor production of mature nodes?

   2. Will American semiconductor manufacturers be able to compete effectively in the global market for relatively commoditized silicon?

   3. Will the application of funds fix the structural issues with lagging edge supply in a sustainable way?

The table is set. The terms and problems are defined. These tools offer everything we need to examine the implementation of the CHIPs Act and the kinds of results possible.

Problem #1: The Leading Edge

The CHIPs Act has always been primarily about maintaining access to leading-edge silicon. It is where Congress allocated most of the dollars ($33B of $50B total), and it is the source of most of the fears of economic and defense dislocation, due to either disruption in Taiwan or China simply outcompeting the Western world. The success of America’s foray into semiconductor industrial policy will be measured on how it impacts the leading edge.

The CHIPs Act Program Office elected to spread the money around to each of the existing players. Their guideline was 5-15% of the capital cost. Per Ronnie Chatterji at Statecraft:

5-15% of the capital cost was the guideline in the report we released in February. For a $10 billion fab, 10% of that, $1 billion, is a huge grant to subsidize some of these projects. Remember that on top of that, there'll be state and local grants, tax abatements, and the investment tax credit that they can use in the federal tax code.

Intel has received the largest (non-binding, yet-to-be-finalized) grant of up to $8.5B from the CHIPs Act Program Office. Between 2024 and 2030, (1a) Intel could plausibly be building the most advanced foundry in the world. When it is scaling to production volumes, Intel 18A will at least compete to be the most advanced node in the industry. But money can’t fix their problems. In fact, Intel has had the resources to pursue leading edge processes for decades. In the last 10+ years, Intel has been limited by their own culture and poor execution. Recently, Intel made headlines for all the wrong reasons after posting a terrible quarter. While confirming hardware issues with some of their x86 products (i.e. the execution issue wasn’t on the manufacturing side that is relevant to the CHIPs Act), analysts speculated that there were also yield issues with the manufacturing tech. Intel was quick to add that their most recent node for Foundry customers, Intel 18A, powered on (August 2024) to give a semblance that the manufacturing side is in order. For this CHIPs Act funding to be considered a success, Intel must continue their transformation, executing on both the technical dimension of making leading edge processes and transforming their business to include a foundry trusted by US chip designers. Transforming their business would likely require opening their process to collaboration with key customers, increasing investment into their IP ecosystem, and adopting a more customer-centric technology development approach.

Meanwhile, (1a) the investments in TSMC and Samsung will not produce the most advanced fabs in the world at their time of construction. Rather, each company will be re-creating a node they have already successfully introduced in their home country 2-3 years before it comes to the US.

Most Advanced Process Node by Company by Country by Year

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(1b) Structurally, not much is different in building leading edge nodes in the US after the CHIPs Act. TSMC indicated their costs are 5X the cost to build in Taiwan, and it is unclear if this one-off investment will lead to any sort of experience curve improvements. Industry and government are already highlighting the need for continued investment.

(1c) If the goal is to build more capacity beyond the 5 nm node that China is expected to achieve, these new fabs will count towards that goal. While exact numbers are not provided, Secretary of Commerce Gina Raimondo expects that, by 2030, these investments could produce roughly 20% of the world’s leading-edge semiconductors. This is a huge improvement over the present 0%. Presumably, the vast majority of the remainder would be in Taiwan with other possible fabs in Japan and Europe. In my own estimation applying some industry math that $20B in Taiwan gets you roughly 100,000 wafer starts per month, the US fabs would have anywhere from 210-540,000 wafer starts per month with these fabs online. (1d) Given the scalable investments and milestone-based approach to rewarding grants, these targets indicate supply can be carefully managed. Meanwhile, the smaller scale of these fabs versus so-called GigaFabs in Taiwan guarantee their unit economics will be worse.

Problem #2: The Lagging Edge

(2a) Considering the entire CHIPs Act enables $50B of government spending, their grants here are limited to a $1.5B award supporting GlobalFoundries and a few hundred million dollar-range grants to key defense and automotive vendors. (2b) GlobalFoundries and possibly Texas Instruments, who indicates their application is still pending, compete in global markets. However, outside those two,  it seems unlikely any other US-based lagging edge manufacturer will be competing aggressively outside US markets. Again, it seems this funding is not intended to enable domestic manufacturers to compete more effectively globally; rather, it is to ensure domestic supply is available for national security purposes. (2c) Ultimately, there is no easy answer for the broken business model in the lagging edge besides subsidization, and Congress clearly prioritized investment in the leading edge with 2/3 of CHIPs funding. Now, legislators, regulators, and the lagging edge vendors await a flood of lagging-edge chips from China’s $45B investment in Chinese domestic competitors.

Grade: C

The CHIPs Act Program Office took essentially 18 months to decide to subsidize the status quo. This strategy gives them some key wins. With some luck and Intel’s execution, the US may be home to the most advanced fab in the world once again—though it remains to be seen if they will become a foundry the industry uses. CHIPs Act investments ensured there are advanced fabs built in the US again (for now). CHIPs’ policies do not address the structural issues with locating fabs in the US; they are simply subsidizing the alleged 5x higher cost of construction than Taiwan. The CHIPs Act had relatively little capital to deploy towards the lagging edge, and it was deployed conservatively with an eye on key suppliers. 

The CHIPs Act bets are understandable and defensible to the American public, but I am left with the feeling that the US has rented the future. Yes, the fabs built here will stay here. But it does not feel that gravity of the industry has shifted. Without CHIPs Act 2, it seems just as likely the next leading-edge fabs will go back to Taiwan. When asked about the long-term implications of government and industry planning fabs, during an interview with Fabricated Knowledge Hassan Khan of the Department of Commerce stated that the intent of each award was to be the “marginal dollar for the majority of these projects.” He continued, “we’re not trying to create something that would not happen otherwise, and like an unnatural way.”

There is a critical difference between “should we build a fab” and “should we put the fab we want to build in the US or in Taiwan,” but isn’t the point of industrial policy to do something that would not happen otherwise? Interestingly, the US is one of the few countries pursuing an industrial policy of subsidizing multiple vendors. In contrast, both Taiwan and now Japan have centered their industrial policy on an alternate approach: putting all their subsidy behind a national champion, giving them the best possible resources to compete globally and own their future. More on that next time.

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A Thorough Inspection

Making a leading-edge wafer today requires several hundred to over a thousand distinct process steps, each representing a chance to introduce a defect. Any given defect can limit or eliminate the potential value of the end-use chips. Semiconductor manufacturing processes with too many defects are a potential company killer. Catching defects as early as possible and quickly fixing them is critical to a smooth rollout, and it relies on frequent inspection (and increasingly, virtual simulations). American citizens should apply similar principles to semiconductor industrial policy, as companies receive billions of taxpayer dollars.

The government has allocated roughly $39B for semiconductor investment in the US—are they spending it wisely? The next several posts are all about frameworks for analyzing the implementation of the CHIPs Act. Annie Duke’s Thinking In Bets introduced me to the idea of resulting: judging the wisdom of a bet purely by its outcome. In games of allocation and skill, she urges readers against resulting. Instead, bettors should consider the quality of decision-making that went into the bet versus solely judging if the bet worked or not. As the CHIPs Act Program Office awards grants, this series will evaluate the quality of decision-making going into their choices. What were the problems in the US semi-manufacturing market such that we are so dependent on other countries? What problems did the government select to address? How well does the application of funds achieve their desired ends? Are the funds going towards permanent or temporary solutions? Today, we will start with a thorough inspection of the state of US semi-manufacturing at the time of the bill becoming a law, circa 2022.

The TL;DR stated strategy of the CHIPs Act:

• Large scale investments in leading edge manufacturing

• New manufacturing capacity for mature and current-generation chips, new and specialty technologies, and for semiconductor industry suppliers

• Initiatives to strengthen U.S. leadership in R&D [Rob’s Note: this is important but a relatively small amount and outside purview of this series]

What You Will Learn

• How escalating fab costs drove industry consolidation

• How US perception of competition with China is changing the definition of leading-edge

• How depreciated fabs made it affordable to put connected chips in everything

• How the business model for older chips is brokens

In Facing Reality, we covered the core problems facing the US: the production of semiconductors, arguably the foundation of our economy and the heart of protecting our national security, is not within our control. We outsourced manufacturing and exist at the whim of foreign governments who may or may not play nice with us.

The second part, Technoeconomic Pillars of Foundry, is a crash course in the business of foundry and the necessary concepts to understand what makes the industry tick. In short, to survive economically a foundry needs 5 things:

• Scale

• High yield 

• Continuing technology development 

• A comprehensive ecosystem of IP and downstream partners

• Customer trust 

Throughout, I have cited how easy it is for contract manufacturing of semiconductors to go wrong if a company gets any of these 5 wrong, which brings us to our first topic.

Cultivating Mass at the Leading Edge

In semiconductor production, scale matters because it enables both return on investment and the funds to invest in the next smallest process technology. Historically, most of the profits were derived from the newest technology because older technology got commoditized quickly. Big margins in iPhone 14 chips; way smaller margins on iPhone 11. That would be fine if the costs to build a fab were about the same from generation to generation. Instead, semiconductor fab costs have gone up exponentially (note the y-axis below is logarithmic). Without profits to drive R&D and CapEx, manufacturers have a nice fab but are out of the technology race’s cutting-edge, high-margin “sexy” chip business. 

Oh, it gets worse. It takes $25B just to play the game, and now you have to fill it with orders. The demand for those orders goes through pretty wild swings (the dot-com bust, the Great Recession, Covid, good and bad economic cycles…), from annual drawdowns of 40% to upswings of 50%. For an industry that is gambling to breakeven over the span of years, a big downswing in demand can wipe out a foundry. (This fact is particularly poignant when the fab does not have a nation’s capital backing it. Hi, TSMC and Taiwan.) 

The scale required to invest in new fabs and the demand risk meant only a dwindling number of players could stay in the game: Intel, Samsung, and TSMC. GlobalFoundries dropped out a decade ago at 16 nm, and by 2021 Intel was at least a full node (~2-3 years) behind TSMC. There was a very good chance Intel was going to lose the scale required to compete with TSMC. No company that has dropped out has ever gotten back in. 

Yet, the chart is outdated; and one development since its publication in 2021 was a major impetus for the CHIPs Act. Note that the chart above was published in 2021, and a company called SMIC had reached 14 nm. SMIC stands for Semiconductor Manufacturing International Corporation, a dry Western name for China’s most advanced semiconductor foundry. With the backing of the PRC’s generous funds, deep desire for self-reliance, and every tool they would need, SMIC has since advanced from 14 nm to 7 nm and 5 nm despite being a Listed Entity by the Department of Commerce. These advancements only seemed to surprise journalists—the industry knew they could use the tools to make smaller transistors, if they’re willing to do so at higher costs (allegedly up to 50% higher than TSMC though respected and informed analyst Dylan Patel believes it is much higher). Moving beyond that may not be possible for SMIC — the technique used to get from 14 nm to 5 nm has a limit to its usefulness and technology restrictions prevent them from obtaining the EUV tools that would enable them to progress. 

That 5 nm threshold is what the Department of Commerce is focused on. There are two ways to interpret the mandate for the CHIPs Act:

1. Ensure the US has a domestic supply of the most advanced logic manufacturing

2. Ensure the US has a domestic supply of logic manufacturing more advanced than China

The CHIPs Act dedicates “approximately three quarters of the incentives funding, around $28 billion, to establish domestic production of leading-edge logic and memory chips that require the most sophisticated manufacturing processes available today”. When a fab already costs $20-25B and growing exponentially, picking which problem to solve is critical: 

• Is the US shifting something structural, to ensure leading-edge always happens on US soil?

• Is the US “renting” leading-edge in the sense that they were the highest bidder this time and may not be in the future? 

• Is having more fabs with better technology than China more important than fewer fabs with the best technology?

• How will inducing supply affect its relationship with demand? How much risk is there of underutilization, accounting for the subsidy reducing costs?

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Lagging Edge Proliferation

Again, the profits and scale mostly chase the smallest transistors. High-performance computing (chips for PCs, servers, and smartphones) are the groupies of Moore’s Law, chasing the latest and greatest technology. But as technology progresses, the older fabs still work, and their value proposition gets intensely interesting when they are fully depreciated.

The tooling inside the fab is the most expensive part. When those tools are fully depreciated, it is effectively only the cost of sand, electricity, labor, and maintenance to continue production. Part of Morris Chang’s brilliance was continuing to keep TSMC’s fabs running forever, finding new applications for them, at a time when the rest of the industry would salvage any useful tools for newer production and sell the rest. The older stuff is in demand by market segments like Automotive and what is now called Internet of Things (IoT). The main advantages of older technology is 1) the tools to design and manufacture the chips are battle-tested and 2) it’s very cheap because the fabs are almost fully depreciated. The chips are great fits for applications that prioritize cost and certainty of the chip’s functions. These attributes are why chips got embedded everywhere, now with the connectivity that we refer to as the Internet of Things. The importance of all of these segments has only grown with time. In 2023, IDC estimated IoT spend at $800B globally. In 2024, IDC estimated the automotive semiconductor market at $40B in 2020, growing quickly to $88B by 2027. 

The design and marketing of these chips was predominantly done by US, European, and Japanese companies, and very few of these products are manufactured in the US. China is making massive investments here with their most recent fund topping $45B. The PRC’s objectives are to, first, secure the supply chain for their nascent and surging EV industry and, second, win every other market globally. Instead of asking Chinese companies to shoulder the capital risk, China has used government subsidy to consistently grow its share of semiconductor manufacturing capacity, largely through adding capacity to older process technologies:

A Broken Business Model

What few industry players expected, however, was that demand for older technologies kept growing. Doug O’Laughlin at Fabricated Knowledge lays this out in detail, including the points about depreciation made above, so I will do my best to summarize the new parts:

1. Around 2014, the newest fabs started using different tools (larger wafers, different materials). This “broke” backwards compatibility, in the sense that now you could not repurpose these tools to do the older jobs. They could continue to do the primary job they were deployed for, and those would get cheaper with time, but foundries lost the built-in flexibility to use them for alternate lines. 

2. In 2020, demand for cars dropped quickly before surging, whiplashing the demand for the chips that make those cars run.

3. The older fabs were essentially full, creating a demand shock.

4. The foundries could not react quickly with more supply. In the short term, they could not repurpose other lines—they were structurally too different. In the longer term, adding more capacity would mean building new facilities and buying new tools. Recall the economics of a new fab with brand-new equipment are dramatically different from a fully depreciated one. 

5. Therefore, to invest with confidence in new facilities building ancient tech, the foundries secured long-term agreements and non-cancelable, non-returnable orders from their customers.

Essentially, the business model broke during the pandemic. Like our country’s national debt, worrying about running out of depreciated fabs was a future problem i.e. somebody else’s problem, until we ran head-first into that problem. Meanwhile, American companies downstream increasingly rely on these chips; without them lines shut down. In 2022, American companies had to choose to either deal with shortages when demand is high or put capital at risk for foundries to expand capacity that still wouldn’t be online for years. 

Turning back to the CHIPs Act:

• How much subsidy is required to get new domestic supply?

• Will American chip manufacturers of mature nodes receiving funds compete effectively in the global market? Or will they mostly exist to satisfy demand requiring US suppliers e.g. defense?

• Will the application of government funds fix the structural issues with lagging-edge supply? Or will additional capacity require more subsidy?

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How to Grade the CHIPs Act

To summarize, here is my scorecard of the problems the Department of Commerce could choose to address:

1. Leading Edge Problems

   1. Will the application of funds create the most advanced fab in the world?

   2. Will the application of funds make the United States the most desirable place in the world to build future leading-edge fabs?

   3. Given the goal of building more capacity at a level beyond what China is believed to be capable of, how much capacity will be generated with the application of funds?

   4. How will inducing supply affect its relationship with demand? How much risk is there of underutilization, accounting for the subsidy reducing costs?

2. Lagging Edge Problems

   1. How much will the application of funds encourage domestic semiconductor production of mature nodes?

   2. Will American semiconductor manufacturers be able to compete effectively in the global market for relatively commoditized silicon?

   3. Will the application of funds fix the structural issues with lagging edge supply in a sustainable way?

Fortunately, the US government has not been completely asleep on these issues. As I will demonstrate, most of the stuff in the headlines is focused on solving Problem #1, while Problem #2 is…uh…brace for impact. In our next post, we will cover the primary options available to the CHIPs Act through the lens of how well each would address these questions (and raise some new ones) and give some preliminary grades.

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Jerry Sanders, CEO of AMD, once proudly proclaimed “Real men have fabs.” While he meant that chip design companies should own their own manufacturing, perhaps we should restate this as real superpowers have hard tech. Now, in April 2024, the major pieces are in place: Intel and TSMC both have “memorandums of understanding” defining the government funding to spur leading edge production. Samsung appears soon to follow. The table is set for the US’ first foray into industrial policy in generations.

My goal with this series is to educate readers about how foundries work, such that they can assess the effectiveness of semiconductor manufacturing industrial policy. Specifically, I am talking about the leading edge of innovation, where all the goodness of smartphones, AI, and the cutting edge of computing goes. The sanctions on China were designed to ensure Western countries preserve a several year advantage in this particular domain over what China can produce on their own. 

Pat Gelsinger’s relentless execution has made Intel a formidable presence in this market, Samsung is reeling but still investing, and TSMC continues to dominate the foundry space with their extremely public, extremely important differentiator: they are a pure-play foundry. 

What You Will Learn

In Part 1, I set up the history that makes this topic so urgent. Part 2 offers a deep dive on what foundries do and why. Like the fundamental forces of nature, these are the fundamental topics that shape every conversation in semis. These topics are quick to grasp at a high-level, but most of the nuance is left to professional conversations. In this post, we will open up the hood on a few of these topics and walk through the mechanisms, math, and connective tissue of the tech and business, including:

1. The value proposition

2. Revenue generation

3. Scale

4. Yield

5. How customers choose foundries

Again, I worked at Intel on the BD team for their custom foundry as late as 2017, which informs my perspective but will not get into its history or the specifics of my work there.

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The Basics of a Foundry

The defining feature of a semiconductor foundry is that it only manufactures semiconductors; it does not design them. It is the Easy Bake Oven; not the goop you put inside of it. This clarification runs in contrast to the business dynamics inherent in Intel and Samsung, who design, market, and manufacture their own chips, a model known as integrated device manufacturing (IDM). 

An analogy from Steve Blank:

TSMC was the first pure-play fab. Morris Chang (founder) described the inspiration for the foundry as follows:

When I was at TI and General Instrument, I saw a lot of IC [Integrated Circuit] designers wanting to leave and set up their own business, but the only thing, or the biggest thing that stopped them from leaving those companies was that they couldn’t raise enough money to form their own company. Because at that time, it was thought that every company needed manufacturing, needed wafer manufacturing, and that was the most capital-intensive part of a semiconductor company, of an IC company. And I saw all those people wanting to leave, but being stopped by the lack of ability to raise a lot of money to build a wafer fab. So I thought that maybe TSMC, a pure-play foundry, could remedy that. And as a result of us being able to remedy that then those designers would successfully form their own companies, and they will become our customers, and they will constitute a stable and growing market for us. -Oral History Interview: Morris Chang | SEMI

Ironically, in the late 1980s, the belief ran that you had to vertically integrate your manufacturing to succeed. Morris Chang’s core insight argued that you could create much more value by separating the two, unleashing innovative design engineers to work on the design side while the manufacturing engineers focused on general-use manufacturing. 

Manufacturing is simply a culturally different domain than is that of design. The hard part of design runs from the insight and creative vision that is often non-linear.

The culture and art form of manufacturing revolves around paranoia. All the little things matter. A dust particle is your enemy. Creative divergence is The Dark Force. Manufacturers follow rules and structures beautifully - robotically beautifully. The culture of design is taste, novelty, and usefulness. The culture of manufacturing is optimization. Of course, the two are deeply interlinked and more cooperative than antagonistic—design shows manufacturing what is desirable, manufacturing shows design what is possible and economical at different scales.

The other big issue: HUGE capital for manufacturing plants versus relatively tiny capital for design companies: Fabulously low capex needed for fabless design semi companies.

The venture capital industry is arguably the most opportunistic group of investors in the world, especially in Silicon Valley. They want very small amounts of capital invested which can subsequently return 500, 1,000, 5,000 times that very small amount of capital. If they must invest LARGE sums - ie, not $5 million or $10 million to properly capitalize a company ($1 billion+), then it becomes geometrically harder to return huge multiples of that capital down the line. So smaller is again, better. 

In the case of a foundry, the capex numbers are massive. Billions. Not millions. The cost is now so high that only TSMC, Intel, and Samsung are investing commercially in leading-edge, and even the IDMs (Intel and Samsung) have shifted their business model to try to capture more foundry business to support their need for scale to keep playing. Chips happen to have the unique properties that make this possible—if you have the right value proposition.

I. The Value Proposition

How does a foundry’s customer make money?

To understand how manufacturers differentiate their tech, we are going to take a detour into what shapes their customers’ behavior i.e. how does a chip designer make profits. So we’re talking about Apple, Qualcomm, and NVIDIA here i.e. companies that only design and sell chips, but don’t manufacture them. Because they don’t have fabs, they are often just called fabless designers. Chips are mostly commodities. Chips physically fit into a socket, so sales teams hawking chips refer to selling chips as “socket hunts”. Their potential customers have a need for a chip and they’re evaluating bids from multiple “commodity” chip sellers. 

Winning a socket hunt is a process analogous to every other b2b transaction, wherein the seller has to be better, faster, or cheaper to win. That framing—better, faster, and cheaper—is strategically ambiguous. There are critical questions about what better means, faster at doing what, etc. which entirely depend on what you’re trying to make. Often there are other constraints, like power or size, that drive if it works best for the kind of device it is serving. While all chips are made with transistors, the chips needed to train an artificial intelligence model are different from the ones needed to control the clock in your microwave. They are different hardware applications.

What are hardware applications?

The job of chips is to make software applications … happen. It’s great that a given chip can process lots of data quickly and accurately - but just processing data is like chewing food without swallowing. So at the verrrry end of the day, the goal here is to render applications so that they satisfy the user. That is… they use applications like Word or Excel or games or zoom or photo editing stuff… in a seamless manner. 

But in this sense, we are talking about hardware applications. The job of a hardware application is to optimally use transistors to form circuits which maximize the performance of those software applications. Here are a few examples:

• Central processing units (CPUs) are great for running lots of different kinds of programs in serial execution i.e. where one computation has to finish before another. Intel is probably the biggest brand still focused on CPUs.

• Graphics processing units (GPUs) are great for running simple programs across huge datasets. Critically, running one computation doesn’t require solving the others first, so it can quickly parallelize the data.

• Application Specific Integrated Circuit (ASIC) is great if you only ever want to run one algorithm so you want every transistor on the board dedicated to doing one thing. As a consumer, it’s unlikely you have encountered these, but they are more common in networking and telecom.

Often the optimal solution in an application category can look quite similar e.g. lots of processors for mobile phones have the same basic components with the performance and price differing in degrees. Of course, many companies have been born by making something new and different. The differences between applications is much bigger than the differences inside an application category. 

AI is hot. How does AI fit into this?

Sidebar on AI. Artificial intelligence (AI) is rightfully getting a lot of buzz. AI is a category of software applications. An AI has to be trained. After it has been trained, it is an AI model. AI models have recently demonstrated capabilities in some fields above what humans have been able to achieve with their own algorithms. Nation states are racing to understand how this capability can be exploited and how it undermines their security. And they are at least notionally “dangerous” (if we’re lucky, they’ll come for the lawyers first). Hence all the paranoia around export laws with scale volume “AI-driven” chip designs and our good friends in China. 

An artificial intelligence model requires massive levels of computation to “learn” from massive datasets. This training process is limited by hardware. This learning process can take literally years, unless you can get better hardware, which can then subsequently reduce the process time to months, weeks, etc. depending on a number of variables. This friction lives at the heart of the export restrictions on selling these technologies to China. The US wants to maintain a several year advantage in these categories, so any hardware that might enable China to build better AI is now restricted to sell there without a license from the Feds that they aren’t going to give out. (China is quite good at extra-legally accessing technology anyway - we just don’t want to let that happen without a modicum of friction.)

When training an AI model, the trainers (designers) want chips that prioritize absolute performance and efficiency over low cost. The aforementioned microwave manufacturer that just wants a chip for the clock only cares about performance as much as if it can keep the time and then wants it to be as cheap as possible. All transistors, but very different application spaces. AI is expected to be a key beneficiary of leading-edge silicon going forward, and we’ll soon cover why they can get so expensive.

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How do foundries develop transistors to match fabless design customer’s needs?

Ultimately, most chips get boiled down to a benchmark level of performance and a cost per computation. Their value proposition comprises three elements:

1. The benchmark level of performance for that application (said another way, in car terms, ‘what is your 0-60 mph time?) 

2. The cost to achieve that performance is competitive i.e. the juice is worth the squeeze

3. The “performance envelope” i.e. how much power does it use, how big is it, how much heat does it generate, etc.

Performance is always relative—you are always being compared to something else— here, ‘else’ is ‘last year's chip’ or the super cheap chips from 5 years ago - they all work; they just work less quickly and/or elegantly as you compare prices and performance from long ago chip architectures. The other big ‘else’ are your competitors also trying to win that socket. 

The value equation must work to win a socket. As in other markets, some chip design companies will go for absolute performance (the fastest processing chip, albeit for a higher per-something price) while others will try to be value leaders. Ferrari vs. Lexus. In practice, most companies pursue a portfolio strategy: a flagship high-end with more, lower-performing products that give customers the flexibility to meet different needs. For example, Apple will make a new chip, but keep selling the old chip in the old design as their value play. Outside semiconductors, this similar strategy is employed by Ford in the best-selling F-Series line, leading with the $80,000 Ford F-150 Raptor R (the one my wife wants to buy despite never spending more than $27,000 on car, having no interest in trucks, and working from home) and the $34,000 Ford F-150 that Ford sells in high-volume to small businesses. Marketing!

Setting aside my wife’s love of military-grade aluminum and back to transistors, many applications benefit from simply having more transistors. As we covered in the first post, Moore’s Law is the process of being able to draw transistors smaller and smaller, such that you can fit more transistors in the same amount of physical space. If your application benefits from more transistors and you can sell more transistors at the same (or cheaper) price than your competitors, your value prop will look amazing because you will meet (or exceed) the performance profile your customers want and your performance per dollar will be great. 

This dynamic plays out all the time in gaming-oriented devices, notably the central processing unit (CPUs) and graphics processing units (GPUs). In GPUs, NVIDIA is always pushing the high-end to perform even better, while charging a premium for it. AMD, their chief competitor in gaming GPUs, cannot compete with the highest-performing GPUs, but they can sell ones that perform at 85% of the leading performance while being 60% of the cost. That’s a strong value prop for many buyers. This competitive dynamic repeats in many application categories, where chip designers seek the right mix of performance and cost. Competition is what drives Moore’s Law and is the mechanism by which higher-transistor count equals more, better electronics throughout our life.

As a manufacturer, the foundry faces similar choices:

1.  The foundry can make new nodes, keep setting new performance benchmarks, drawing transistors smaller and smaller. This translates to big profits in the long run, if not necessarily the short run…, as the companies with the highest value applications will seek out any hardware advantage they can get and are willing to pay for that level of performance. 

2. A foundry can also cost-optimize existing manufacturing lines (iterating on a current node or adding another flavor to a node to target different applications) to get the performance per cost just right to maintain its attractiveness.

All of this is ultimately abstracted in the industry to PPA: power, performance, area. Power indicates if it fits in your performance envelope. Performance is usually how fast the transistors can toggle on-and-off in some application-specific mode. Area is how much space it takes up. Area for a long time has been a proxy for cost. Remember, smaller transistors are generally better, so you want density to go up while area goes down—that gives you physically smaller chips, so you can fit more on a wafer, and you get more product for the same cost per wafer. Sometimes you’ll hear this as PPAC now, breaking out area and cost, because smaller transistors are not necessarily cheaper going forward.

II. Revenue Generation

Most foundry revenue comes from selling wafers. Customers want those wafers cut into chips, but for reasons we’ll get into later, the smallest unit of sale is usually a wafer - think: you don’t buy one egg at Safeway, let alone Costco. 

The two critical numbers that define your profit contribution metrics are the number of wafers (scale) produced and revenue per wafer. To get those numbers, a foundry will get a sense for the number of customers who might be interested in the new process technology, smoke some ayahuasca to learn what volumes and prices might be for the next decade, and place a bet if it will be a greater cash on cash investment return than other places they could invest that $40B (or if Tim Apple tells you to do it, or if the Taiwanese government tells you to do it so they can tap into some Dark Brandon Energy, etc.). Moore’s Law means this bet has historically paid out, as long as the tech actually works.

III. Scale

Let’s set up an example foundry on paper to show why spending $40B on an Arizona fab is still attractive to TSMC. They are doing this enormous build today, often building several at a time. Of course, spending $40B reveals a belief that the investor is going to get a return greater than $40B on that factory. 

How do foundries measure scale?

Embedded in that $40B is an assumption that this fab is going to be a high-volume fab, likely targeting 50-100,000 wafer starts per month. Think about a wafer start as making a pancake at Denny’s when there is a union strike. The pancake goes on the grill Tuesday at noon and you get served Thursday night. So wafers take ages to get set to be made at scale - they then get cut up into chips but the whole process takes so long that the industry standard metric is all about wafer starts - if you know the number of horses at the starting line, you’ll impute some lesser number after yield fails at the end. 

It’s not practical to scale up or down a fab after you’ve built it, so you’re making this decision early. Everything in semiconductors is about confidence and reducing risk of not getting a return on the massive investment. As for why 100,000, I don’t have a firm answer but I assume that number has become something of an optimization point based around the physical constraints of the number of tools required as well as the economics of the newer plants. Smaller plants are available at 45,000 or so, but those tend to be for older nodes where costs and revenues are smaller. And I return to the fact that this is entirely a scale business - like other things in dating and kaiju, larger is better and the higher volumes then amortize the initial high fixed costs of building the plant and the capital costs much more efficiently. 

How do new nodes affect the scale of a company’s operation?

TSMC’s average revenue per wafer in 2021 was about $4,000, spread across 291 distinct process technologies. A process technology is the size and scale you draw transistors at, so they can draw transistors for money 291 different ways. Pricing is always closely held, but often analysts and industry insiders can back it out. At launch in late 2022, TSMC’s 4nm node was reportedly going for $17,000 per wafer. At the time, about half of TSMC’s revenue came from technology released in the prior 5 years. The $17,000 flavor wafer delivered the smallest transistors in the world; the chips coming out of this system deliver massive value to the end customer which the wholesaler then (or retailer in Apple’s case) can upcharge consumers for.  The disparity between the $17,000 for a new process technology and the average revenue per wafer of $4,000 illustrates how quickly older technologies become commoditized, how expensive new process technologies are, and how having a differentiated technology is how to recognize outsized profits. The horrible truth is that scale and revenue per wafer are highly correlated—those who execute well in delivering process technologies that are better, sooner than others get the demand from customers. In effect, they leverage their scale advantage in a kind of “winner take all” business map. Note that TSMC’s market capitalization even after the market fallings in 2022 and China sniffing around their borders is $641 billion.

How do the economics of new nodes work financially?

I promised numbers, so let’s look at the first 3 years or so of a new technology. Today (T-3), you place your bet for $40B. You won’t see profit, let alone real revenue, for 3 years (T1). You’re designing your factory for 100,000 unit sized production slates, but if it’s brand new, it definitely will not be running at peak capacity right away. Instead, you’re going to scale up to 100,000 wafers per month as your team gets more comfortable. The plant managers decide to start at 50% utilization, i.e. they are only going to produce 50,000 wafers per month to start and slowly scale up to >90%. Both numbers are based on how TSMC operates their tech over time, often not starting production until they can achieve 50% utilization and topping out around 90% after it has reached maturity in a few years. Each process technology is different, requiring new tools, and the utilization is often a function of how quickly you can master those tools.

Simple financial model: I have emphasized the marginal revenue and cost per wafers. The plant’s wafer costs are pretty much flat, meaning that wafer 1 costs the same as wafer 10,000 in the volumes the plan calls for. And for now, just completely ignore depreciation, taxes, and the cost of providing childcare to operators and technicians.

Fundamentally, the plant is buying processed silicon sand for ~$500 and selling it (after a ton of very high IQ work) for ~$17,000. The business on paper is beautiful. It’s almost software, or something analogous to a CD or DVD stamping business. In practice, TSMC makes about a 50% gross margin across all their lines. They define gross profit margins as revenues minus the costs of revenue which includes costs of equipment, labor, and materials directly used in manufacturing, excluding operating costs like R&D, G&A, and marketing. I recall they seek about 80% contribution margin on new process technologies in their first year of production, so cost per wafer is likely closer to $3,400 per wafer with a floor at process maturity less than $2,000 per wafer (averages 50% margin on wafer revenue of $4,000).

TSMC will have had a couple years to reap some big profits. At the high-end, Apple, NVIDIA, and others want to pay for performance as soon as they can get it. TSMC will sell as much as they can before competing foundries at Samsung and Intel bring their tech online in 3-4 years, when prices for similarly dense, powerful and light $17,000 style wafers … will decline (note how prices decline in T3 and T4). As for how low TSMC’s prices will decline…I have no idea. If their average revenue per wafer is $4,000 but the newer stuff is inherently more expensive with less competition, maybe the prices stay higher longer? I left it at $10,000 after T5 and I will leave it to the reader to make their own scenarios for higher or lower.

If TSMC is good and lucky, they will be close to recovering their cash investment in year 4. Here’s a guess at how that simple foundry might work out to T10. While I modeled the loaded marginal cost per wafer as flat, in practice, their buildings are on a 10–20-year depreciation schedule while the machinery and equipment is on a 5-year schedule. There would be some savings to loaded marginal cost per wafer after T5 as a result.

At $17,000 per wafer and a cost of $3,400 per wafer, that’s 2.9 million wafers required to recover a $40B investment, ignoring all the exogenous stuff. Just to frame these volumes: TSMC manufactured about 14.2 million wafers total in 2022, representing an estimated 24% market share of 59 million units in the whole market.

Beyond just recovering their capital, TSMC also has to plan for the future. Moore’s Law marches on, and TSMC’s customers expect them to lead the way. By T1, TSMC will have already had to invest in building a fab for their next-smallest process technology. By T3, they’ll just be recovering their investment and will start on the generation beyond that. The margin for error is slim.

Where does wafer demand for a new technology node come from? Why isn’t everyone doing this?

When you make a new process technology, some of your customers will choose to stop making the stuff they were making before. The new entrant elbows out the margin for the makers of that product who are less-than-awesome at doing so. For TSMC to make a new production technology, some of the expected 2.9 million wafers will come from the 14.2 million wafers you already make. Some of the volume will be all-new, though, which will only add to your total wafer production across all lines.  If it were all new wafers, the new production technology would represent a 2% increase to TSMC’s total capacity. Now, this 2% might not sound like much, but historically, making this transition has been enough to scare away all about 3 players, TSMC, Intel, and Samsung. Assuming they could even get the capital to attempt it, the others are terrified because there’s so much that can go wrong, including:

• Timelines could slip. Delays in construction, obtaining requisite tools, and developing expertise with those tools to reach performance milestones can all increase the risk that you will never recover the investment.

• Your competitor could master the new technology faster than expected, reducing the revenue potential of the new investment.

• The customer bringing you that early version decides they don’t want to buy as many and your volumes crater (or their customers get tired of your incremental updates and decide they can wait longer for a new one). In fact, having that first customer (your anchor) is essential to attaining the scale you need to ever recognize a profit on your fab. There are only about 4-5 anchor customers in the world, with Apple the clear #1 and NVIDIA a bitter #2. 

  • Note that China has several aspiring anchor customers, like Huawei. At least, these were anchors in a globalized economy, where they have access to the best technology and Western markets (and steal and subvert and…) It’s a matter of debate if they’ll remain anchors, though they are now shoving any demand they can spare to the aspiring Chinese foundries.

From a traditional business perspective, think about the grocery store’s choice of selling Diet Coke for $7 a 6-pack where they make 20 cents a unit versus selling capers for $15 where they make $9. They’ll choose Diet Coke every time because DC’s volumes are MASSIVE relative to caper bottle sales. However… If somehow the market price of that Diet Coke dropped 45 cents, the grocery store is now losing 25 cents a pack for the privilege of selling it. So it’s … risky. 

What does it look like if this bet goes wrong?

To give a sense of how this looks when things go sideways, let’s visit the other end of the talent pool: GlobalFoundries (GF). Until 2008, GF was the manufacturing arm of AMD, who was designing, marketing, and manufacturing their own products. I have emphasized trust several times, and TSMC emphasizes it in their own annual report. GF exists because Intel (allegedly) committed some…light…anti-competitive behavior, significantly undermining AMD’s ability to generate revenue and the scale necessary to keep investing in competitive technologies. (Note I did not join until 2011, so this was recent-ish to when I was working on chip design strategy at Intel but it wasn’t anything I had any knowledge or visibility into.) The FTC would ultimately settle with Intel, but it seems the damage was done. In such a competitive environment, it’s not hard to consider it a small price to pay to cripple your most significant threat. AMD needed the manufacturing assets off its books, and its manufacturing arm would have to stand on its own. GF was born. The consequences for Intel are still playing out, as fabless companies know Intel can be ruthless towards competitors.

GF would continue to introduce new process technology for a few years, until badly dropping the ball with Apple. In 2014, GF “bought” IBM’s fabs (IBM wanted these assets off their books so badly they gave them an exclusive contract to continue production of IBM chips plus $1.5B to take them). In 2016, to try to keep up with Intel and others, GF licensed the latest technology from Samsung. By 2018, GF announced they wouldn’t make any smaller process technologies and continue to optimize and refine the larger technologies. As of 2024, their smallest process offering is 12nm.

Bigger is better. Scale wins. But we’ve yet to introduce the most important metric—the only metric those in the silicon mines really talk about: yield.

IV. Yield

What is wafer yield? Why is it so important to semi manufacturing?

Moore’s Law is all about being really good at drawing small transistors. Research labs can in fact draw transistors at much smaller scales than what’s produced in volume. The research labs are not very good at it, so only a few of the ones they draw actually work. These research projects are important technical demonstrations that illustrate potential technology paths for manufacturers, but the research only matters if you can do it at scale. Things that work in a lab under non-commercial and extremely controlled conditions don’t necessarily translate into commercial production facilities that make chips profitably.

When a factory produces chips, it makes them in the form of giant 20” diameter wafers which are then cut into, say, 100 die which are (usually) packaged into 100 chips. Said another way, one wafer produces 100 chips. And many of those chips are broken or don’t work as expected. One dust particle ruined that production run. One burst of electrons from the solar flare changed the magnet system on the flux capacitor and other chips didn’t work. Fifty other things can go wrong here. Lots of accidents happen when flying at these speeds. So when you produce a wafer that would notionally carry 100 chips, the actual useful yield from that wafer is… less. Generally, the smaller the transistors, the higher the error rate.

Yield is defined as the number of functional chips produced in a given manufacturing run, divided by the total number of chips that were attempted to be produced during that run. Previously, I stated that the foundry charges by the wafer, not the chip. The foundry’s customer defines what functional means and, critically, has most of the levers to change the design to improve the number of functional chips and the degree to how well chips function. Performance is rarely binary but continuous. Again, these companies are selling a portfolio so even though it might not perform like a $300 chip, it’s still saleable as a $200 chip. Therefore, the foundry’s customer carries the risk of poor yields.

Ultimately, it’s a partnership to do your best and make the economics work. It is not uncommon for the first attempt to be zero-yield—i.e. no working chips. Learn and repeat. Sometimes, customers want to push the yield risk onto the foundry by only paying for good die. Foundries will accommodate customer requests as much as they can, and there are no good data on terms of agreements, but most major deals I am aware of are for wafers.

How does wafer yield affect semiconductor manufacturing economics?

Let’s add yield to our calculation. For their high-end iPhone chip, the A16 Bionic chip, TSMC can fit about 492 chips per 12” wafer. Let’s start with a processing run where everything runs perfectly, and the fab plant produces a wafer run with 100% yield and TSMC recognizes $17,000 per wafer of revenue from Apple:

The cost works out to $35 per chip. What happens if we plug in a realistic first year yield?

In that first year, the customer is paying the same amount to the foundry per wafer but only getting half as many “good” chips, so the cost per chip is essentially double. Recall that the value proposition covers three things: 

1. The benchmark level of performance for that application (said another way, in car terms, ‘what is your 0-60 mph time?) 

2. The cost to achieve that performance is competitive i.e. the juice is worth the squeeze. 

3. The “performance envelope” i.e. how much power does it use, how big is it, how much heat does it generate, etc.

Poor yields increase the cost per functional chip. The poorer the yield, the worse the value proposition gets for a foundry’s customers as well as for the foundry. This is predicted and hedged as much as possible, but the newer the process technology, the higher the uncertainty around yields.

That first production period is known as risk production, where a foundry is still learning what works and what doesn’t. Reportedly, Apple’s rather basic requirement is >50% of the chips have to work. Foundry customers can only bear so much cost increase before it’s uneconomical to sell, so they limit production while yields are poor. Apple and TSMC work together to relentlessly maximize yields. Errors are tracked down with brute force and complex diagnostic tools and by run number 30, yields are over, say, 40%. Lather, rinse, repeat and after 8 months, yields on this new cutting-edge wafer production facility can kiss 80%.

As yields go up, it becomes more economical for more customers to come on board. Ideally, the fab manufacturer is simultaneously increasing max wafer starts per month, improving yield, and controlling the price per wafer. Even better, if your competitors are yielding poorly, you can keep your rates high and recognize more profits longer.

What is required to improve yields?

Answering this question in detail would require several graduate degrees that I do not have. The short version is:

• The best photolithography tools, which today come from ASML in their Extreme Ultraviolet (EUV) product lineup. Today, these products produce wafers the fastest at the highest scale with the highest yields at the smallest transistor size.

  • China explicitly was barred from using these tools, which essentially limits the commercial viability of the products they can make. Yet, China has continued making smaller transistors. How? They use older technology (Deep Ultraviolet aka DUV) that’s slower, more defect prone, etc. The yield is reportedly pretty good, but it’s inherently more expensive and will have practical limits. Good enough if you just want better transistors for the military though.

• Tribal knowledge about how to use the tools (Morris Chang loves talking about the importance of TSMC’s seasoned operators and technicians, with extremely low employee churn rates)

• Good process design kits, a software tool given to chip designers that describe the “rules” of manufacturing for this new technology before it exists. 

How has yield shaped the foundry market?

In the lead up to the CHIPs Act, US semiconductor manufacturers struggled with yield. Intel had a disastrous attempt at yielding their 7 nm process technology (which at the time was called 10 nm but was since re-branded to 7). GF was so bad at yielding new process technologies that Apple had to take all their iPhone 7 volume to TSMC. Of course, GF gave up on harder process technologies as a result. 

Again, this is a business about confidence and reducing risk. When companies have stumbled this poorly, would you bet your company on their success? 

V. How Customers Choose Foundries

I have touched on how hard it is to produce chips profitably, at scale, and with high yields…. and why fabs must win volume to survive and profit. Here is what those chip designers care about in a foundry partner:

1. Technology development: Technology development (TD) derives from scientists and engineers planning their design or ‘draw’ of transistors. Success in technology development is about:

   1. Transistor performance: There are different kinds of transistors for different kinds of hardware applications. TD creates essentially catalogs of different kinds of transistors with different performance characteristics that map to the application categories they’re interested in.

   2. Yield: This is about setting rules that the customers—the chip designers—can easily implement to achieve good yields, fast.

   3. Timeline: Can this process be implemented at scale on the requisite timeline?

   
   The job of the brilliant PhDs working in technology development is to create the blueprint for customers to get an appealing value proposition that the manufacturing guys are confident they can build. If they create an enticing value proposition for customers, but it’s so error-prone that manufacturing can’t build it, what was the point (👀 IBM)? Getting technology development is so critical to performance that even companies that don’t manufacture their own products employ their own teams to teach fabs how to optimize the supplier’s process technology for their chips.

2. Manufacturing capability:  How many wafer starts per month are available? When will it be online? Where is production occurring geographically—is it close to the rest of the customer’s value chain? Is it in a politically sensitive region? A foundry’s manufacturing discipline in both controlling the production environment and tracking the process over time can impact your ability to keep yields high. 

3. Ecosystem: There is a massive ecosystem of IP and electronic design assistance (EDA) tools to help fabless chip designers get to market quickly. The best comparison I can draw here is to the tier suppliers in the automotive industry. You don’t need to reinvent the tire to make a new car, you just need to pick which kind of wheel and tire best matches your car’s use-case. The EDA tools help you do that and integrate it into your design and into the foundry’s design rules.

4. Trustworthy customer service: A foundry is ultimately in the service business. A fabless design company is handing them the keys to the castle, including all their IP and their roadmap, entrusting they will give them functional wafers years down the line that they can monetize. While technology is important, building semiconductors is a game of trust and confidence. Can you and will you do what you say you’re going to do? Pushing Moore’s Law forward is hard enough, (and it may be broken and who really cares? Moore’s Law just meant that chips would get better, faster, and cheaper for a long time and they did). 

   While technology is important, building semiconductors is a game of trust and confidence. Can you and will you do what you say you’re going to do?

   A pure-play foundry is the only one that can definitively answer that they will always put customers first. Alternatively, an IDM has their own products to consider. Any IDM asking a fabless designer to let them manufacture their products is effectively asking them to put the life of their company in the hands of someone with all the resources to compete with them. Worse, they could simply not prioritize their wafers. This fear is often more theoretical, as IDMs are often looking to sell capacity to areas they don’t want to invest design resources into…though of course if that market gets attractive enough someday? At an IDM, customer #1 is always the internal customer. At a pure-play foundry, customer #1 is whomever has the most resources.

Ok, that’s the crash course in leading-edge foundry. When it all goes wrong, you get GlobalFoundries. In part 3, we’ll use this framework to analyze what American taxpayers are actually subsidizing and how to assess the success of the industrial policy going forward.

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The problem is relatively simple: semiconductors, arguably the foundation of the US economy and military strength, are not in our control. US-based semiconductor production capacity has collapsed in the last 30 years, dropping from 40% of global semiconductor fabrication in 1990 to 11% in 2019. 

To be crystal clear, the process of feeding our hungry computers with chips involves really 2 broad processes:

1. Creating the chips (designing them)

2. Manufacturing them

The first job takes lots of smart electrical engineers and knowledge about that particular application space; the second job is what this blog series is about. 

At this point, many bits have been spilled about global semiconductor manufacturing, the CHIPs Act, and the risks of centralized production in Taiwan. What I hope to add to the noise is a unique perspective: someone who had a small role in Intel’s attempt to build a foundry. Of course, I am not going to be getting into anything confidential—it’s for someone else to write the history of ICF. Rather, I am drawing on that experience to provide a framework for non-experts to understand the dynamics and incentives for semiconductor manufacturers going forward. I started this series in late 2022 i.e. before NVIDIA blew up, to convince investors to care about semis and specifically semi manufacturing. That’s…less of a problem sitting here in 2024, with $NVDA at roughly 4x from where I started privately publishing this. 

Now, I want to update and add to this series with some public posts. Over the course of the series, my goals are:

1. To educate investors, technologists, and citizens why you should care about semis and manufacturing specifically

2. How the manufacturing side of the business actually works 

3. Frameworks for assessing the different options presented by governments and industry

4. Why there is still a big opportunity for a US-based pure-play foundry

I find the more I write, the more I have to say. I will do my best to break this up. I expect to provide updates over time analyzing how the CHIPs Act is progressing towards its goals.

Your Humble Author

To add a little detail to my perspective, I was on the go-to-market team for Intel Custom Foundry from 2015 through early 2017. During this time, Intel established a foundry, though it was extremely nascent, interesting to investors, and not a significant revenue driver. If you knocked on Intel’s door during this time and wanted to buy some Moore’s Law, you would be talking to my bosses. I cannot emphasize enough how junior I was on that team, but I got to learn a ton of how it actually works. Because Intel was not really in the business of selling their manufacturing capabilities, I was part of the team that turned tools into products, developing the messaging and positioning for Intel’s core technologies and preparing the business development team for conversations with customers. I had the least experience in foundry, which was useful in that I was willing to ask basic questions and learn things from first principles.

I am most definitely not a dark wizard of semiconductors. Dark wizards know every layer of the stack, the physics, the chemistry, the roadmap, and every inch of the manufacturing plants. They don’t just talk to the rocks, the rocks answer them. Many of you might know dark wizards—I do and learned everything here from them. One was gracious enough to read this through for me, though if a dark wizard were to correct anything here, they are almost certainly correct.

If you are unfamiliar with semis, what follows is a crash course in the situation, the players, their objectives and incentives, and their challenges. If you are already familiar with semis, treat this as a refresher on how we got to this moment.

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Basic Terminology

Let’s start with some terms. Manufacturing chips is all about making transistors. A transistor is just a kind of simple electrical device with two possible states, 0 or 1. Semiconductors are a group of materials on the periodic table, which includes silicon. Semiconductors as a material were found to be an exceptional way to make transistors—there are no moving parts, the power needed is really low, and it is cheap to make many of them because you are making them by etching away what you don’t need with a chisel of light. The process of etching with light is known as lithography. Putting it together, we use light (lithography) on semiconductors (almost always silicon) to form boatloads of transistors with the collective goal of processing data faster, better, cheaper.

Put all those transistors together and conceptually, you have a circuit. When you put many circuits together, you get a die. If your dies are small enough, you can fit a lot of them on a wafer. Wafers are cut into individual die that are packaged into chips.

A wafer is a big round disc of silicon that you’ve etched a bunch of transistors into. When a manufacturer is “fabricating semiconductors”, it typically means they are producing wafers that their customer will have sent somewhere else to be cut into chips and put into devices. Plants that pump out wafers are known as fabs (short for fabrication facility). This taxonomy is so fundamental, that I’m going to reiterate the Russian nesting doll allegory to more clearly illustrate the picture. Think of the ecosystem extant on a semiconductor. Going from largest to smallest, we have: fab → wafer → chip → circuit → transistor → electron. These are all made out of a semiconductor material, silicon, that’s been doped up more than an Alameda Research analyst.

More transistors = more raw computing power. If you can fit more transistors onto a wafer (or a chip), it gives you a lot of computational, business and other options. For example, you can increase the performance of your chip, by shipping more transistors, keeping the price the same. Or you can keep performance the same and fit more chips on a wafer, lowering your overall costs. Lower costs can empower you to lower prices and take more market share or keep the margin for yourself, depending on if your competitors can do the same thing or not. The value equation of performance to cost is why there is such an economic incentive to be able to draw transistors smaller and smaller. It’s also why all the naming schemes for new technology use smaller numbers the newer the technology, because the size of the transistors you draw are smaller.

That new, smaller number often represents an entirely new manufacturing process, what the industry calls a node. Any given manufacturer might have similar but not exactly the same way of producing transistors at that size, so node comparisons often focus on transistor performance and size rather than the specifics of the tools used in the manufacturing technology.

Moore’s Law outlines the process of introducing new ways of drawing smaller transistors i.e. making new nodes. In the late 60s, Gordon Moore predicted that the processing power of a given chip would double about every 18 months… and for a half century, generally speaking and miraculously, it has. The result are badass charts like this, where things Moore’s Law touches get cheaper (and, in our lived experience, much better and faster) and things that the US government touches get more expensive:

That newest node is known as the leading edge. Because the industry works so hard to keep making smaller transistors, the leading edge is a moving target. In 2024, it stands that you can roughly double transistor count every 24-48 months, which has slowed from its heyday in the 1990s of doubling transistor count every 18-24 months. If you want even more context about semiconductors, check out Steve Blank’s primer.

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The Collision Course of Semiconductors and Geopolitics

The key area in which we have “failed” lately has revolved around making the smallest possible transistors, at scale. This collapse is most notable where Intel fell behind the Moore 2.0 curve. Through 2022, Intel was as much as 2-3 years behind TSMC without much hope to catch up. In this chart, published in 2022, notice how Intel is still at 10 nm, while Taiwan (TSMC) is at <10 nm. This chart is what the US semi industry used to lobby Congress to give them money, as it legitimately set off alarms. Congress was also getting yelled at by their constituents to do something about the chip shortage, but there was not much they could do because so little production was in the US.

Specifically, this chart means that Intel is building bigger (which is by our definition NOT better) chips at 10 nanometers… and TSMC is building at scale meaningfully smaller chips - think: 3-5 nm…ish. Note that Intel and TSMC use slightly different numbering schemes because the numbers are mostly a representation of how small transistors are now for marketing purposes vs. being literally the size of a feature on a transistor. With respect to transistor feature sizes and performance, TSMC 7 and Intel 10 are regarded as about equivalent. Since its publication, Intel actually re-branded their 10 to 7 to try to eliminate this confusion, but it makes historical discussions like these a mess.

As of 2021, Taiwan Semiconductor Manufacturing Company (TSMC) produced 92% of the most advanced logic silicon in the world, in addition to a substantial portion of older but still important technology. Since the chart was published, the world is a little different. Intel managed to stop their decline, finally shipping Intel 7 née 10, as well as Intel 4 née 7 and Intel 3, a slightly improved version of Intel 4. In 2024, Intel expects to ship 20A, another new naming convention. The A in 20A stands for Angstrom, 1/10 of a nanometer. Intel will be shipping 20A or “2 nm” which is, for marketing purposes, comparable to TSMC’s 2 nm they are now shipping. You can imagine the pissing match between CEOs to claim if they’re really comparable. Samsung, the primary manufacturer in South Korea, has continued to push ahead albeit behind the more aggressive TSMC and Intel, with their 2 nm product expected to launch in 2025.

All of that is just about the leading edge, where process technology moves quickly and new plants now routinely cost $40B. Few companies can afford to invest this amount, which led to consolidation of manufacturers of leading-edge technology. However, the older processes making larger transistors matter too, as evidenced by the numerous chip shortages in automotive companies. They only use older processes. The older processes are affordable and useful when you don’t need cutting edge performance or cost. 

I likely don’t have to tell anyone in the finance and investing community that China isn’t big on democracy right now, if you did any business with Hong Kong. The Chinese Communist Party has similar feelings about Taiwan, where I just highlighted is home to the vast majority of our semiconductor production capacity. Chris Miller’s Chip War is the definitive history and examination of the technological and geopolitical forces that shaped the modern semiconductor industry and the inherent risks of centralized production in Taiwan. Taiwan and TSMC now plan openly about what will happen to their production sites in the event of a Chinese invasion. Americans can confidently assume that, if Taiwan was invaded, it would take 3-5 years for us to replace that semiconductor supply, likely longer in a war-torn world. The shortage of semiconductors would ripple through our economy and come at a time when our military would need chips the most. 

For Taiwan, semiconductors are a shield. Taiwan’s success is attributable to directly subsidizing semiconductors, highlighting a broader trend. The capital (both financial and intellectual) is so dear/ high/ at scale… that the business war here is no longer fought by a single company; it is fought by nations. Japan, South Korea, and a host of other key players have stepped forward to own their destiny with chip manufacturing industry. 

TSMC and Taiwan’s industrial policy have out-executed everyone in capturing this space. The nation of Taiwan does not play fair: It intentionally shifts every rule it can shift so as to favor its own nation’s semiconductor manufacturing prowess, including direct subsidies of land, facilities construction, and R&D. We can’t blame them - we do the same thing and in the 100 Meter ScrewYou Proprietary Race, Apple is in the lane between TSMC and Microsoft every Olympics. 

Of course, the US has jumped into this race with the CHIPs and Science Act passed in 2022. The federal government pretty much had to because American manufacturing companies simply failed to anticipate or adapt. The cost and uncertainty of building anything in the US didn’t do us any favors either.

As mentioned before, Intel should have owned this domain but failed nearly fatally, as GlobalFoundries, IBM, and Texas Instruments all essentially quit trying to continue investing significantly because it was too hard, too expensive, and there were other profitable ways to build products on older processes. That groups’ operations remain but they have ceded the most powerful part of the market. There was no other American competition - Intel should have run the tables. But they didn’t because they missed making chips for smartphones. When Intel encountered the new smartphone paradigm, they prioritized protecting their software ecosystem known as x86 instead of embracing the size of this new market. (x86 is another new term that references the instruction set architecture which is roughly how software programs talk to the chips.) The software ecosystem ensures only their chips can be sold into those applications, which is great for fat margins and big competitive barriers (see: NVIDIA with CUDA). Their failure to anticipate or address mobile opened the floodgates for Apple, ARM, and TSMC to build a new ecosystem bigger and better than Intel’s. 

Intel’s mistakes were not necessarily a bad thing for the US. Intel would primarily design and manufacture its own products, a business model known as integrated device manufacturer or IDM, such that they competed with nearly everyone. TSMC however only manufactures semiconductors, a model known as foundry—they will offer their capacity to (nearly) anyone and will not compete with their customers. Much more on that topic in the next episode. TSMC’s ascendancy benefited many other American companies, who now had access to silicon processes that rivaled what Intel could make. The feeding frenzy for Intel’s market share was on.

Intel has been grappling with this mistake for over a decade. Before Pat Gelsinger, the board attempted to protect Intel’s profit margins while its scale and market share declined. This spiral is suicidal in the semiconductor industry. The natural conclusion of this path would be to break up Intel, similar to AMD’s fate. The manufacturing assets would become a pure-play foundry while the design side would be a fabless chip designer that can work with any foundry. By hiring Pat Gelsinger, the board decided to try to avert this path. Gelsinger has made it clear he wants to keep Intel together at a scale that would set Intel to be a leader. Notably, he has Intel executing extremely well, but they are still only challenging for the crown while core parts of their business face strong headwinds. Critically, Intel has done all of this without CHIPs Act money—leadership matters.

One popular option for bringing the leading edge back to America is using American political leverage to have TSMC build more plants here to satisfy US demand, to ensure continuity in US supply. TSMC’s recent investments in the US are a reflection of that. While they are a political concession to Apple and the Biden administration, I believe they will be net good for the US. The new plants will create more jobs for technicians, spur suppliers to invest more deeply in our supply chains, and place in the US more of the critical next-gen tools required to build the best performing chips. However, these investments aren't going to significantly shift production from Taiwan. Said another way, TSMC does not want serious competition and it will desperately go out of its way to stem the tide of “fair play” competition. Duh. Welcome to America. Our best companies do the same thing. At least Japan has succeeded in getting them to diversify more in their country than fully centralizing operations in Taiwan.

Presently, these various strategies are on a collision course. If we are to change our destiny as projectiles of TSMC, we need to change our tune, or at least have one as it relates to mass scale manufacturing of cheap chips. The CHIPs Act is a nice start. The gist is that we need a real, leading-edge foundry here in the US. Intel believes it can be that foundry, but their business model asks customers to trust a powerful competitor with the core of their business in an industry where only the paranoid survive.

The price tag for a leading edge fab starts at roughly $40B. Think about the $40B+ price tag: it is 1/3 of the price California wants to pay for high-speed rail. Think of how small this number is in the scheme of all the things we spend money on… and how important it remains for us to control the fate of our own semiconductors.

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Pop-science is something of a wonder. Growing up in the 90s, Bill Nye was the face of science. In the 2000s, Malcolm Gladwell’s books made scientific results ever more approachable and showed the persistent demand for explanations of scientific results into modern times, the same as A Brief History of Time (1988), Cosmos (1980), and even The Origin of Species (1859) before it. Neil deGrasse Tyson rode the advent of social media to be the face of pop-science in the 2010s. Tyson’s success, in particular, set off a few waves in different directions. One wave went further into the pop side of pop-science, with fans following memes like Yeah, science bitch, inspiring accounts that generate and monetize the content. The uber-nerds bookmarked XKCD (before the feed existed) and built their own social media sites like LessWrong to slate their desire for more technical and data-driven discussions. The content creators took to YouTube to bring the technology to life, like this stunning case study of blue LEDs:

Another personal favorite, Asianometry, documents how history, geopolitics, and technology are intertwined. Business professors update their courses with new examples and phenomena to cover, merging neuroscience, psychology, and marketing. Bro science races through podcasts. Even throughout the Enlightenment and the industrial revolution, I am not sure science has ever had more content, more eyeballs, and more money to be made from explaining theory and data.

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This ecosystem has hummed along through the replication crisis. If you have paid attention to science at all, this crisis is not news to you. Many social sciences (notably psychology and behavioral economics) are struggling to replicate some of the foundational research of their field. In the early 2010s, it was identified as a full-fledged crisis for the fields. To be clear, this is not about fraudulent papers. The social sciences are inherently difficult to study because people are difficult to study. People grow and change, and societies completely change. One way I think about the replication crisis is that it is about understanding the present prevalence and effect size of historical behavioral and social phenomena. The medium of the replication crisis is the same as the leading edge of any science:

1. statistics and letters to the editor in journals

2. the scientific news groups that study them

3. the niche internet haunts and watering holes for the professionals that care about understanding and implementing research

The experts in this space will flat out tell you most science is not written for a lay person to understand and is part of a larger conversation the lay person is not part of. Little of that translates to the realm of science as entertainment anyway. Its worst form is grifters spinning up debates that “Science is a liar sometimes”:

Ultimately, you are on your own to follow the space and interpret the results—or rather, determine which experts to listen to when they clash. The books are still for sale, though maybe they get a new edition with a defense of the work. Many (but not all) Wikipedia pages mention replication controversies now. The science-y social media accounts target what gets eyeballs and will continue to post whatever entertains people. Maybe you know some grad students in the field who will tell you where the scientific consensus stands. Maybe you are reading the writers you trust on Vox, LessWrong, or Astral Codex Ten who happen to cover the issue (or cover someone else covering the topic).

At best, when you encounter some cool behavioral research, you develop a habit to ask: does it replicate? Then you google “<social phenomenon> replication”, parse the results, and attempt to remember in the weeks and months after if that survived replication or if it was constrained at all. As someone with an engineering but not research background, I found this process all deeply tedious and draining—it’s far too easy for simple stories to travel and too hard to retain the nuance required for real understanding.

So I started writing down what I learned, from where, what I wanted to remember from all that reading, and thought it worthwhile to share to save others that time. This is replicateornot.com.

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What is the goal?

Replicateornot.com provides a simple resource for lay people dedicated to tracking if and how well the most-discussed science concepts in books, marketing theory, and pop culture replicate so they can update their prior beliefs accordingly.

Why is it called ReplicateOrNot.com? 

Part ode to HotOrNot.com, part something I could remember.

Who are you to comment on the scientific consensus if something is successfully replicating or not?

My friend with a degree in psychology: “just because you (Rob) can’t understand something doesn’t mean it’s bullshit. That would invalidate… well, most of science to be frank.” 

This is truer than I want it to be. I do not pretend to be a part of the scientific debate; I am far downstream. I make no claim to truly understand the scientific consensus either, as I understand it happens as much in the hallways of research labs as the journals on the web. I am just writing down what I found, what I took from it, why I came to that conclusion, citing my sources, and jumping on the ego grenade that is Cunningham’s Law so anyone else interested in this can benefit.

Many of these conclusions are weakly held, and I welcome input from those more directly involved.

Will Replicateornot.com cover the whole replication crisis?

For now, that is not the goal. I just want to cover the stuff that is the most viral, that shows up on reddit and Twitter the most. 

Why is Replicateornot.com so ugly?

While I am inspired by other bro-science fighters like Examine.com, I thought it best to go fast. When I saw another post praising simple-if-ugly designs, I decided to ship it and make it pretty and detailed if people like it.

What are your criteria for assessing what replicates and what does not?

I made a few broad categories drawn from how I saw the researchers discussing the implications of replication attempts. I am at heart an empiricist: I care what works. If new theories guide me to try something I wouldn’t have and it works, I am pleased because it works (or works better than it worked before). If a new paper shows the effect size for something isn’t as big as predicted but it works for me, I will keep doing it. If it provides a useful framework for understanding the world, I will continue to use that framework, knowing there are others that could also apply. While entire studies may not replicate exactly or generalize to the whole world, I want to emphasize both the parts that are still true and understand any proven limitations.

Should I assume the replication crisis is evidence academics are trying to lie to me?

No. The physical universe itself is pretty consistent except for all the times it’s not, and studying people is even more difficult. Academic fraud is a real issue but a separate one. The issues of replication tend to be related to the methodology or limitations of the theories developed in response to observed interactions.

Your beliefs are bad, and I want to correct them. How can I do so without hurting your feelings?

You are a saint. Please drop a note in the comments here, shoot me an email at main@replicateornot.com, or tag me on Twitter @replicateornot. 

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I am an engineer by training with the questionable instinct to run towards problems, especially problems that should not be problems. When I heard that the United States could not produce sufficient 155 mm artillery shells to supply Ukraine, I thought it sounded odd. I knew essentially nothing about artillery save I would not want to be on the other end of one. I was generally aware the industrial base for the defense industry had either atrophied or specialized or both, depending on your perspective. Maybe this was just over-specialization? A dependency on a single part? Maybe it is a reliance on something exotic? Surely, there must be an explanation, something that would help me understand why we are so ill-prepared. Maybe there is some new technology that could be applied? This is a record of what I learned for the benefit of a more-educated citizenry and to save time for anyone else investigating the issue.

Maybe as Much as You Ever Wanted to Know about Artillery Shell Production

I approached this first to understand and second to know if-and-how I could help. My understanding is far from perfect—I went for breadth more than depth, often sacrificing detailed measurements in order to go fast. This is the short version.

• There is a shortage because our lone factory’s maximum capacity is 28,000 units (i.e. 28 ku) per month in the face of Ukraine asking for 600,000 units (600 ku) per month.

• The major shortage is with producing steel casings for the artillery shells.

  • The materials required to make these shells are relatively plentiful.

  • If you were to remove the casings bottleneck, other bottlenecks are possible. However, the next step (filling shells with explosive materials) is simpler to optimize vs. moving and precisely shaping a hundred pounds of steel at 2000°F. 

• There is no technological shortcut to producing more of these. 

  • 3D printing is not viable. The metal itself is too precise to be printable with current technology, and the size of the shells would pose an issue.

  • Existing facilities use automation, but newer facilities will integrate more automation to improve quality and throughput.

• Producing shells requires specific machine tools to accommodate the weight/heat and specially forming the nozzle. The tools themselves are fairly common, especially the furnaces; however, a factory optimized for building shells won’t be effective at building much else.

• The existing production facility is part of a national landmark district, complicating expanding the existing facility.

• The Department of Defense’s (DOD) current primary path forward is building a new facility in Garland, TX with modern automation and inspection equipment. Assuming it is contributing to the goal of scaling to 100ku per month of production by early 2025, it will have taken 3 years since hostilities started and 2 years since a contract was awarded for it to be online.

• Building additional capacity is largely in DOD’s hands, as defense contractors are unwilling to build facilities without long-term (15 year) contracts. Today, the DOD typically awards 3-4 year contracts.

Ultimately, I am left with the impression that the US’ solution to problems that require building things is to avoid it at all costs. Congress is loathe to fund munition supplies that are never used, and defense contractors are loathe to build factories that sit idle (and despite what Hollywood may portray, everyone wants deterrence, not actual conflict). Though Congress and DOD are funding a new facility, 3-4 years will have passed before it produces a shell, which is entirely unhelpful in a present conflict. Instead, the DOD is attempting to plug the Ukraine-sized hole with shells from allied nations including Canada, South Korea, Finland, and Germany—places where it’s still possible to build new things.

I believe in alliances, especially when it is the free people of the world standing against aggression from authoritarians. What troubles me here, though, is that the US is pursuing that option because the domestic defense industrial base, inclusive of DOD and its contractors, is sclerotic. It treats time like it’s free. It does not respond quickly. It does not build or innovate around current problems, because of a combination of disincentives from DOD’s own structure and the pervasive challenges of trying to run a manufacturing business in the US. These are largely own goals. If the DOD would write longer term contracts. If we did not declare essential production facilities to be historic landmarks, strangling expansion. I did not even want to get into why GOCOs exist or the labyrinth of DOD procurement, but it is sufficient to say they both pose challenges to doing anything new or different. My solace is that in a real conflict, all of that red tape would be put to the side and people can get about building things. There will be a multi-year lag between when that crisis happens and how fast the factories can return, and I hope we can weather that storm.

Could an entrepreneur change this equation? Anduril’s success is a testament that with the right application of influence and creativity, new companies can compete effectively against the prime contractors. I am less certain that is a possibility here for a few reasons. The primary concern is getting an ROI in 3-4 years on the capital required to build such a facility. You either need a technological edge that dramatically reduces the capital expense, or you need to be able to blend production with other commercial goods (i.e. dual use). For the former, I do not see a dramatically cheaper option unless there is some arbitrage on cheaper electric arc furnaces and presses. For the latter, 3D printing could be an answer, if the material properties existed. However, metal 3D printing companies are struggling with sales as-is, reflecting a lack of commercial demand for commercial 3D printed metal parts. Therefore, even with the steel needed, I am confident it would be a battle to keep them full the rest of the time. This only gets harder without a technological edge like 3D printing, as it would be a sub-scale, commodity steel mill likely optimized for an application with only one real customer.

The rest of the post is specific research questions I had with the best quality of answers I could find and cited. Questions include:

• What is the 155 mm artillery shell?

• How big is the gap between what we can produce and what is needed?

• What does the supply chain for 155 mm shells look like?

• Where’s the shortage?

• How are casings made?

• Can 3D printing help?

• What kind of tools are used in the existing process?

• What is the maximum capacity for the existing infrastructure?

• What’s the yield among existing producers? Can it be improved?

• Can they expand existing facilities?

• If they’re going to get to 100ku per month by 2025, how are they going to do it?

• How long does it take to set up a new plant? Why?

• The need for 155 mm shells is unique to European wars. Why worry about this if the risk is a war in the Pacific?

• In a direct conflict, what would we do?

If you see anything incorrect or do additional research, please let me know.

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Much More Than I Ever Wanted to Know about Artillery Shell Production

What is the 155 mm artillery shell?

Throughout the war in Ukraine, the 155mm shell has been a weapon of choice. Without air superiority, the 155 mm shell combines range, lethality, fire rate, and mobility to project force up to 20 miles. With small, cheap drones spotting for them, the army of Ukraine was able to consistently halt quantitatively superior Russian advances. 

So what is it? It is a 3-part device consisting of a steel body, explosive filler, and a welded rotating band. It can also be fitted with different pieces of tech for specialized roles. The image above shows a variant with a base-burner attached, which extends the range. Other versions include a GPS tracker on the nose to serve as a precision-GPS guided munition.

How big is the gap between what we can produce and what is needed?

No defense department is going to say flatly what their true supply or demand is, so consider these numbers illustrative. 

• Ukraine claims they have productive uses of up to 600ku per month.

• Pre-Ukraine war, the US made 14ku per month.

• In February 2023, they claimed their primary production site is capable of 1,000,000 parts and components annually or 83ku parts monthly. 

  • This number is ambiguous if that directly relates to 155 mm shell components and is likely aggregating total production across all lines, including lines not related or useful for producing 155 mm casings.

• As of June 2023, the US was making 24ku per month.

• As of September 2023, the US was making 28ku per month. At the time, the DOD stated a goal of making 100ku per month by early FY 2025, and it claims to be ahead of track towards that.

  • The EU is also ramping production, as they expect to need much more artillery in a direct conflict.

    ---

What does the supply chain for 155 mm shells look like?

Update: To be specific, I am focusing on the US production line. Note that the US also buys these shells from allies. Many allied countries can produce them and have shared stockpiles with Ukraine, including Canada, South Korea, the United Kingdom, Germany, and Norway.

The supply chain for 155 mm shells starts in Scranton, PA at Scranton Army Ammunition Plant, where the steel casings are made. Iowa Army Ammunition Plant is responsible for filling the shells with explosives. 

Both of these facilities are GOCOs—government owned, contractor operated. Essentially, the government owns the plant and the equipment, and the contractor bids for the right to operate it and sell the parts back to the government. General Dynamics runs Scranton AAP, while American Ordnance operates Iowa AAP.

Where’s the shortage?

Every media report of the shortage cites casing production as the limiting factor in US production.

How are casings made?

The casings themselves used a special form of steel, called HF-1. HF-1 has a fascinating history, winding through the National Academy of Sciences to Bethlehem Steel. 

HF-1 is a high-silicon, high-carbon, high-manganese form of steel. The basic requirements of an artillery shell are that it must withstand great force to be launched, before another explosion breaks the shell into fragments. The first force—launch—requires a high yield strength, such that the metal won’t deform (yield) under that pressure. In the vernacular, yield strength = yeet distance, while the fragmentation characteristics of the metal relate to the lethality. HF-1 was selected because of how predictable it shatters while maintaining a high yield strength. Everything you could ever want to know about this steel and its competitors is available in a report that Bethlehem Steel put together in 1973: Producibility of Artillery Shells Made from HF-1 Steel available here: AD0763988.pdf (dtic.mil)

Additionally, Military Times visited the factory and put together a good video of the process, minus the technical details but plus a lot of the operational details:

Roughly, the process is:

1. Precisely cutting 20’ lengths of steel scrap into billets

2. Billets are heated to 2000 °F

3. Billets are pressed into shape

4. Billets are cooled and shot-blasted

5. Billets are polished

6. Copper bands are added

7. The billet’s nose is heated and formed to shape 

8. Metal is heat-treated again before an oil bath

9. Casings are polished and washed again

10. Casings are given threads to fit fuses and rifling of the barrels

11. Casings are treated with phosphate, painted, and set aside for transport

    ---

Can 3D printing help?

Given my experience in the 3D printing industry, this question was top of mind. A core problem for DOD and the defense contractors is that they have to build custom production lines to surge demand. But if there’s no conflict in Europe, these machines are mostly idle. 3D printing is essentially a line designed to be changed much faster, as you can make many different shapes. In theory, with a fleet of metal printers, you could be making war components when necessary and making commercial parts in peacetime. They would almost certainly be more expensive than a dedicated production line, but if the US doesn’t want to pay the capital for it, at least this would be an option. Unfortunately, the short answer is no, 3D printing can’t help here, at least not with today’s technology. 

I am not aware of any metal 3D printer capable of making HF-1 steel or any other high-silicon, high-carbon steel. Metal 3D printing is still pretty limited with some vendors offering questionable material properties that are not attempting to touch high-performance steels. It makes sense the machine vendors wouldn’t prioritize a metal without much commercial appeal.

The other operative question is if a shell casing would fit in the build volume of a current 3D printer. Given the shells are 858 mm in length and 155 mm in diameter, they fit in the build chamber of Velo3D’s 1MZ printers (315x1000 mm and 600x1000 mm), though it looks like they exceed the existing build plate options. In that orientation, they would also have an extremely long print time.

What kind of tools are used in the existing process?

The Army overview page for the facility lists the following:

• Multiple long stroke vertical hydraulic forge press lines

• Capability to produce large mortar projectiles

• In house metallurgical testingIn house metallurgical testing

• Over 120 hydraulic tracer and CNC lathes

• Machining capability exceeding current ammunition manufacturing requirements

• In house end-to-end production processes, no outsourcing requirements 

• Multiple automated paint lines 

• Multiple heat treat furnaces that austenitize, quench, and temper

From a 2017 brochure covering SCAAP’s capabilities: Scranton brochure 2017 Final.pdf (army.mil)

What is the maximum capacity for the existing US infrastructure?

In February 2023, the US Army released some information about SCAAP: SCAAP is a leading producer of large-caliber artillery metal parts and components and can effectively and efficiently manufacture runs from small batch quantities to more than one million annually”. 1mu annually would be a little over 83ku per month. Of course, in PR speak, they didn’t say they could make 83ku 155 mm shells per month—presumably they can make 83ku of something, maybe a mix of things, if all their lines were running flat out.

Given the US was flatout at the end of 2024 at 24ku per month with existing infrastructure, I assume all of that was coming from Scranton AAP. In 2022, the US government authorized an additional $243 million to “help ramp up production lines and help put in some new equipment that will allow the plant to be able to produce more shells at a higher rate”. I assume some of that money went to scale production from 14ku to 24ku per month, but I can only guess how much remains to be added.

What’s the yield at Scranton AAP? Can it be improved?

If you ask in the right rooms, the answer you get is there is room for improvement. Allegedly, the site’s structure as a GOCO disincentivizes optimizing yield. The contractor gets paid the same for operating it as-is, and if the government wants to fix it up, they would have to put in the time and energy.

Can they expand Scranton AAP?

Beyond the existing retrofits, you must be willing to let go of some history. Scranton AAP started life in 1908 as a steam locomotive erecting and repair facility. With trains on the decline, it was established as an army ammunition plant in 1953 but sits in a larger national historic district and is listed on the National Registry of Historical Places. I imagine it is a spectacular testament to when we used to build stuff.

If they’re going to get to 100ku per month by 2025, how are they going to do it?

Build a new facility somewhere else. In December 2022, the US Army gave General Dynamics a contract to build a new facility in Garland, TX. Apparently they have a nice spot picked out in a …business park?

Update: I was preparing this from notes, and the Garland facility was my primary focus, as it’s still General Dynamics. However, the Army’s press release from 2022 also mentions a facility in Ohio operated by IMT Defense Corporation. The two will compete for the contract.

How long does it take to set up a new plant?

The contract was awarded in December 2022, 10 months after hostilities broke out in Ukraine. It is now February 2024, and the DOD is saying we’ll be at 100ku by early 2025 with little other information about the ramp up.

Considering they want to get to 100ku by early 2025 and SCAAP operating at full capacity at 28ku, the new facilities would add 72ku total. Assuming an even split, each would be producing 36ku or 130% the capacity of SCAAP each by early 2025, more than 2 years after the contract was awarded and 3 years after hostilities began.

Why does it take so long to set up a new plant?

“What takes the longest is acquiring and installing the machine tools and the machinery that makes the explosives and things like that,” Bush said during a media roundtable. Additionally, permitting is difficult, construction labor is tight at the moment, and there is no incentive to go faster, especially if US political will is waning in the face of Republicans viewing Ukraine’s independence as a gift to their rival Democrats.

The need for 155 mm shells is unique to European wars without air superiority. Why worry about this if the risk is a war in the Pacific?

The issues with 155 mm shell production are a case study of the issues that are endemic in the defense industrial base. In January 2023, Center for Strategic and International Studies documented the many deficiencies in the defense industrial base. It includes all manner of missiles needed for such a conflict.

In a direct conflict, what would we do?

To be clear, we would continue to rely on our allies in all circumstances, as supply chains allow. For our own production capabilities, I imagine something that looked more like Operation Warp Speed to develop the COVID vaccine, where the government no longer treats time as free. We have many of the machines required in the US; these would need to be co-located to be dedicated to a war effort. The permitting issues would evaporate, and the DOD would award contracts of whatever length to justify the facilities. With the tools and raw materials, the next question is having the right mix of people and automation to operate the tools. In a crunch like this, you would likely have more people initially while you quickly automated what you could. Training those workers would be key.