High AI valuations are not universally crazy. Similar to the early internet era, some companies will inevitably go to zero while others, the future 'Googles' of AI, will prove to have been undervalued. The critical skill for investors is distinguishing between hype and long-term potential.

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 market's reaction to Big Tech earnings shows valuations are unmoored from traditional metrics. Microsoft soars on an efficiency narrative while Google is punished for similar spending. This volatility stems from a sentiment-driven market trying to price a paradigm shift it doesn't fully understand.

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 extreme demand for Cerebrus's IPO, despite valuation warnings, indicates the market is in a hype-driven phase where investor appetite for any AI stock is so high that traditional fundamentals are temporarily irrelevant, setting the stage for other major AI IPOs.

The stock market's enthusiasm for AI has created valuations based on future potential, not current reality. The average company using AI-powered products isn't yet seeing significant revenue generation or value, signaling a potential market correction.

Because AI companies' growth is incredibly volatile and hard to project, their massive valuations aren't based on traditional cash-flow analysis. Instead, they trade like "memes" or narratives where value is driven by news cycles, making them better for short-term trading than long-term holds.

VCs are paying astronomical seed valuations (up to $200M) for AI infrastructure startups from 'legible' founders (e.g., ex-OpenAI). This high-risk strategy mirrors the 2021 market, where investment decisions are driven less by business viability and more by a VC's capital and access to play in a consensus-driven space.

In the current AI hype cycle, a common mistake is valuing startups as if they've already achieved massive growth, rather than basing valuation on actual, demonstrated traction. This "paying ahead of growth" leads to inflated valuations and high risk, a lesson from previous tech booms and busts.