Leopold Aschenbrenner's fund, despite a strong AI thesis, was margin called due to massive leverage. This shows how short-term market corrections, amplified by leverage, can destroy fundamentally sound, long-term positions—a classic lesson Warren Buffett has warned about for decades.

Investor Leopold Ashburner's bullish AI thesis may ultimately be proven correct. However, his fund was wiped out by a forced liquidation due to excessive leverage. This highlights that correct long-term predictions are worthless without proper risk management that can withstand short-term volatility.

Today's massive AI company valuations are based on market sentiment ("vibes") and debt-fueled speculation, not fundamentals, just like the 1999 internet bubble. The market will likely crash when confidence breaks, long before AI's full potential is realized, wiping out many companies but creating immense wealth for those holding the survivors.

The current AI boom mirrors the dot-com era. The underlying technology is revolutionary and will transform the economy, but valuations may have already priced in decades of future growth. This means investors buying now risk poor returns even if the companies ultimately succeed, as both technology enthusiasts and valuation skeptics can be correct simultaneously.

Investor Howard Marks notes that every major technological revolution, from railroads to the internet, has produced a money-losing bubble. The current AI excitement, characterized by the belief that "no price is too high" and that rules have changed, mirrors the psychology of past bubbles, suggesting extreme risk for investors.

The startup landscape now operates under two different sets of rules. Non-AI companies face intense scrutiny on traditional business fundamentals like profitability. In contrast, AI companies exist in a parallel reality of 'irrational exuberance,' where compelling narratives justify sky-high valuations.

The AI boom can sustain itself as long as its narrative remains compelling, regardless of the underlying reality. The incentive for investors is to commit fully to the story, as the potential upside of being right outweighs the cost of being wrong. Profitability is tied to the narrative's durability.

While the AI capex boom may seem unsustainable, the mechanics of shorting it (e.g., buying puts) reveal the extreme difficulty of the trade. The bet requires being correct not just on the eventual downturn but on its precise timing. The risk of losing the entire premium makes it an unattractive risk-adjusted bet.

Financial firms tend to create thematic ETFs (e.g., AI, Clean Energy) after a sector is already hot and asset prices are inflated. Investors buying into the theme often arrive just as a market correction is imminent, leading to poor returns.