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Leopold Aschenbrenner's AI hedge fund unwinds after a brutal semiconductor drawdown

Illustration for the Aschenbrenner fund collapse story

The man who wrote the AI boom’s most-quoted manifesto just watched his own fund fall apart on an AI trade.

Leopold Aschenbrenner, a former OpenAI researcher, became famous in 2024 for “Situational Awareness”, the essay that convinced a lot of Silicon Valley that the AI buildout was underpriced. He then launched a fund on that thesis with roughly $225 million from backers including Patrick and John Collison, Nat Friedman and Daniel Gross.

The drawdown

According to CNBC, assets that stood near $45 billion at the start of July fell to roughly $10 billion in a matter of days, on tumbling semiconductor stocks and mounting margin calls, at leverage reported as high as 400%. He was forced to unwind the entire public book, including SK Hynix and CoreWeave, selling at a discount to Ken Griffin’s Citadel.

The detail that made the story travel: the unwind landed while guests were arriving for his wedding.

Not a zero, he says

Aschenbrenner has pushed back on the obituaries, and this part matters. He says the fund was not liquidated after the forced unwind, and reported unaudited returns of minus 67% for the month against plus 80% year to date. TechCrunch also reports the fund still holds its Anthropic shares.

So the accurate description is a brutal drawdown and a destroyed public book, not a zero. Those are different outcomes, even if they photograph the same.

The lesson in the leverage

Being right about a technology and being right about the trade are two different jobs. The thesis behind the fund was not obviously wrong; the AI buildout it bet on is still happening. The leverage was the problem. At 400%, a sharp move in semiconductor stocks does not test your conviction, it removes your ability to hold the position at all.

Is this a crack in the AI trade itself, or just one over-levered book meeting a volatile week? The distinction will matter to everyone else still running the same thesis with less margin.

Sources

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