The chokepoints.ai atlas: the AI-compute value chain, layer by layer.
When SpaceX listed, up to a third of the float was earmarked for retail. By then the prize had already been settled: early investors and more than 4,000 employees were millionaires before the first public share traded, around 400 were centimillionaires, and a handful were billionaires. That is how most of the obvious AI winners have gone too. The gains were made in private, years before anyone outside could buy in.
Which makes the useful question a different one: where did the prize go for investors who could only buy public stocks? The market answers it cleanly.
01 Where the prize went
If you’d invested in the S&P in 2013, you’d have 5x’d your money in 13 years. Not bad, but a more concentrated NASDAQ bet would’ve yielded 8.1x.
All sounds great, until you see that investing in an index of the top 10 stocks would have yielded 113x, a 40+% IRR, easily beating most top-quartile hedge funds. (Obviously you’d have had to keep tracking the top 10 as it changed over the years, but it’s useful as a thought exercise.)
Almost a dream: 113x on $10k makes you a millionaire in 13 years. That is, unless you’d gone all in on Nvidia and made a staggering 684x in that time frame.
Growth of $100 from Jan 2013 · log scale
The whole market returned 5×; the single chipmaker at the chokepoint returned 684×. Note the log scale: each gridline is 10× the last. Source: public market total-return data, Jan 2013 to Jun 2026; top-10 basket equal-weighted, rebalanced as constituents changed. Chart by chokepoints.ai.
The effect only amplifies from 2025 onwards: investing in the AI picks and shovels has made Leopold Aschenbrenner 12x on his money (1000% net of fees), and a SanDisk pick would’ve yielded 34x in the same period.
Growth of $100 from Apr 2025 · log scale
The same pattern, faster: SanDisk is a holding in Aschenbrenner’s book. Log scale. Source: public market total-return data, Apr 2025 to Jun 2026; fund figure as reported. Chart by chokepoints.ai.
Notice the direction of travel. The whole market made you 5x, big tech 8x, the ten giants 113x, the single chipmaker 684x, and the infrastructure names since 2025 more still. The alpha was never in the apps. It compounded one layer down: in the compute, the power, the memory. When compute was the chokepoint, Nvidia and its virtual monopoly won. When memory became the chokepoint, SanDisk won. When electricity was the chokepoint, Bloom Energy won.
We’re sceptics of our own convictions and quite reserved investors, but even then we’re up 80% YTD on actual portfolio net worth, not just a tiny pot.
The authors’ portfolio, year-to-date rate of return, account value redacted. Brokerage screenshot, 2026. Past performance is not indicative of future results.
Reading Issue 000? chokepoints.ai is a weekly research note on the AI-compute supply chain: where the bottlenecks are, and which companies benefit from them.
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02 What this is
Though the majority of foundation model opportunities have stayed private for a while, there are thousands of public companies further down the AI supply chain that you could’ve bought into, and we’re here to help you find the next batch.
With the chokepoints.ai tool and newsletter, we’ve mapped the end-to-end AI value chain, its 2,376 dependencies, and the 17,500 companies within it, so that you can understand what the core drivers, barriers and opportunities are. More importantly, we’ve highlighted the 95 chokepoints: the areas within AI where the bottlenecks are greatest. Over the next few months, we’ll be dissecting these even further to build a more comprehensive view of both the strength of each chokepoint and its geopolitical status.
Our objective is NOT to
Help degens yolo into stocks.
Promise 1,000% returns year on year.
Give Twitter influencers ammo to copy.
We serve only to
Educate you on what the full AI stack looks like.
Open the discussion on interesting investment ideas in the space.
Give the world a better dataset for the space: which skills, sectors and geographies are worth knowing.
03 Who we are
As co-authors, we’ve been fortunate to live in this world for a while now, one of us as a machine learning researcher at one of the UK’s leading AI labs, the other active in the Effective Altruism and AI safety movements since first year of undergrad at Oxford.
The chokepoints thesis has shaped bigger decisions than where we invest:
Building and running the AI team at a top-decile private equity fund.
Getting deeper into the x-risk AI safety movement, working with a range of organisations.
04 Why we bother
A word on why we bother, because this is a pillar of the whole project and not an aside.
There is an evolutionary mismatch between genes that change over generations and the exponential rate of progress in AI, and it is the core driver of humanity losing its status as the most powerful entity in the world. Just as we evolved from primates and eventually overpowered them, AI has evolved from humans and may overpower us.
The chokepoints are where the leverage is: the points at which this technology can still be steered, slowed, or governed. They are also where the returns are, and that is no coincidence. Scarce, hard-to-replace positions are what markets price and what policy pulls on. Understanding them is the best way to make sure that you benefit from the technology rather than lose out to it.
We take that seriously. It is precisely why we would rather you understood this infrastructure than looked away from it.
Whether you’re just getting started in AI or investing, looking to start or buy a business, or managing billions, we’re here to give you a real understanding of the picks and shovels of AI, one level deeper than the chips: the places the market has yet to price properly.
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Disclaimer. Chokepoints is for informational and educational purposes only. Nothing in this newsletter or the chokepoints.ai tool constitutes financial, investment, legal, or tax advice, an offer or solicitation to buy or sell any security, or a recommendation of any investment strategy. Always do your own research and consult a qualified financial adviser before making investment decisions. The authors may hold positions in companies or assets mentioned, and may buy or sell them at any time without notice. Parts of our research and writing are produced with the assistance of AI tools, which can make mistakes. Despite our review, figures, facts, and sources may contain errors, so verify anything material before acting on it. Past performance is not indicative of future results.
About the charts. Growth-of-$100 figures use public total-return market data; the top-10 basket is equal-weighted and rebalanced as constituents changed, as a thought exercise rather than an investable strategy; multiples are rounded. The fund figure is as publicly reported. The portfolio figure is the authors’ own brokerage screenshot, June 2026. Every chart reconstructed by chokepoints.ai.
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