Major tech companies are investing in their own customers, creating a self-reinforcing loop of capital that inflates demand and valuations. This dangerous practice mirrors the vendor financing tactics of the dot-com era (e.g., Nortel), which led to a systemic collapse when external capital eventually dried up.

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 proliferation of billboards for highly specialized, unintelligible B2B companies along Silicon Valley's Highway 101 signals market froth. When advertising shifts from consumer brands to obscure B2B2B services, it suggests excess capital is flowing deep into the tech stack, a classic sign of a potential bubble.

The dot-com era was not fueled by pure naivete. Many investors and professionals were fully aware that valuations were disconnected from reality. The prevailing strategy was to participate in the mania with the belief that they could sell to a "greater fool" before the inevitable bubble popped.

A genuine technological wave, like AI, creates rapid wealth, which inherently attracts speculators. Therefore, bubble-like behavior is a predictable side effect of a real revolution, not proof that the underlying technology is fake. The two phenomena come together as a pair.

The dot-com era saw ~2,000 companies go public, but only a dozen survived meaningfully. The current AI wave will likely follow a similar pattern, with most companies failing or being acquired despite the hype. Founders should prepare for this reality by considering their exit strategy early.

Marks emphasizes that he correctly identified the dot-com and subprime mortgage bubbles without being an expert in the underlying assets. His value came from observing the "folly" in investor behavior and the erosion of risk aversion, suggesting market psychology is more critical than domain knowledge for spotting bubbles.

The memo flags deals where money is "round-tripped" between AI players—for example, a chipmaker investing in a startup that then uses the funds to buy its chips. This practice, reminiscent of the 1990s telecom bust, can create illusory profits and exaggerate progress, signaling that the market is overheating.

The institutionalization of venture capital as a career path changes investor incentives. At large funds, individuals may be motivated to join hyped deals with well-known founders to advance their careers, rather than taking on the personal risk of backing a contrarian idea with higher return potential.