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.

Following George Soros's theory of reflexivity, markets act like thermostats, not barometers. Rising AI stock prices attract capital, which further drives up prices, creating a self-reinforcing loop. This feedback mechanism detaches asset values from underlying business fundamentals, inflating a bubble based on pure belief.

Phenomena like bank runs or speculative bubbles are often rational responses to perceived common knowledge. People act not on an asset's fundamental value, but on their prediction of how others will act, who are in turn predicting others' actions. This creates self-fulfilling prophecies.

During the bubble, a lack of profits was paradoxically an advantage for tech stocks. It removed traditional valuation metrics like P/E ratios that would have anchored prices to reality. This "valuation vacuum" allowed investors' imaginations and narratives to drive stock prices to speculative heights.

Howard Marks uses Warren Buffett's framework—'First, the innovator, then the imitator, then the idiot'—to describe the predictable lifecycle of investment trends. A strategy begins as a good idea for a few, gets copied by the masses, and eventually becomes an overcrowded, risky trade for latecomers.

Investors often invent compelling secular narratives—like a permanent housing shortage or "Zoomers don't drink"—to justify recent price movements. In reality, these stories are frequently post-hoc rationalizations for normal cyclical fluctuations. The narrative typically follows the price, not the other way around, leading to flawed trend extrapolation.

The modern internet economy runs on an "attention market" where viral narratives attract talent and capital, often independent of underlying business fundamentals. This accelerates innovation but risks misallocating resources toward fleeting trends, replacing traditional price signals with attention metrics as the driver for investment.

In a late-stage bubble, investor expectations are so high that even flawless financial results, like Nvidia's record-breaking revenue, fail to boost the stock price. This disconnect signals that market sentiment is saturated and fragile, responding more to narrative than fundamentals.

Philosopher Jean Baudrillard's theory of "simulacra"—where representations become independent of reality—perfectly models the meme stock phenomenon. The stock's price becomes a "third-order simulacrum," taking on a life of its own driven by narrative, detached from the company's actual performance.