Similar to the dot-com era, the current AI investment cycle is expected to produce a high number of company failures alongside a few generational winners that create more value than ever before in venture capital history.

The current AI boom is driving valuations to unprecedented highs across all stages. While this creates opportunities for massive companies, it also creates significant risk for founders who may struggle to raise subsequent rounds above their large liquidation preference stacks if they don't achieve breakout growth.

The AI era's high velocity of change, where market leaders can be displaced in 1-2 years, resembles the volatile dot-com bubble, not the last decade's predictable SaaS growth. This means founders must consider that even massive scale doesn't guarantee durability, making exit timing a critical strategic question.

Current AI investment patterns mirror the "round-tripping" seen in the late '90s tech bubble. For example, NVIDIA invests billions in a startup like OpenAI, which then uses that capital to purchase NVIDIA chips. This creates an illusion of demand and inflated valuations, masking the lack of real, external customer revenue.

The current AI boom may not be a "quantity" bubble, as the need for data centers is real. However, it's likely a "price" bubble with unrealistic valuations. Similar to the dot-com bust, early investors may unwittingly subsidize the long-term technology shift, facing poor returns despite the infrastructure's ultimate utility and value.

AI companies raise subsequent rounds so quickly that little is de-risked between seed and Series B, yet valuations skyrocket. This dynamic forces large funds, which traditionally wait for traction, to compete at the earliest inception stage to secure a stake before prices become untenable for the risk involved.

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.

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.

The current AI funding climate is characterized by massive seed rounds raised on long-term vision alone, with no concrete near-term plan. The process has become highly transactional, forcing investors to make decisions in under a week, preventing deep diligence or the formation of a true partnership with founders.