Jeff Aronson warns that prolonged success breeds dangerous overconfidence. When an investor is on a hot streak and feels they can do no wrong, their perception of risk becomes warped. This psychological shift, where they think "I must be good," is precisely when underlying risk is escalating, not diminishing.

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.

When a company's valuation is based on profits projected decades into the future, it reaches a critical point. Investors eventually stop buying into even more distant projections, causing a stall as they wait for reality to catch up or sell to others who still believe.

Today's market is more fragile than during the dot-com bubble because value is even more concentrated in a few tech giants. Ten companies now represent 40% of the S&P 500. This hyper-concentration means the failure of a single company or trend (like AI) doesn't just impact a sector; it threatens the entire global economy, removing all robustness from the system.

Success in late-stage venture resembles trading more than traditional investing—it's about buying and selling on momentum. However, this "new public market" has a critical flaw: while liquidity exists on the way up, it vanishes on the downside, making it impossible to execute a true trading strategy when a correction occurs.

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.

Financial models struggle to project sustained high growth rates (>30% YoY). Analysts naturally revert to the mean, causing them to undervalue companies that defy this and maintain high growth for years, creating an opportunity for investors who spot this persistence.

While AI investment has exploded, US productivity has barely risen. Valuations are priced as if a societal transformation is complete, yet 95% of GenAI pilots fail to positively impact company P&Ls. This gap between market expectation and real-world economic benefit creates systemic risk.

Rapidly scaling companies can have fantastic unit economics but face constant insolvency risk. The cash required for advance hiring and inventory means you're perpetually on the edge of collapse, even while growing revenue by triple digits. You are going out of business every day.