The severity of the dot-com crash was so profound that in 1999, a venture capital fund that simply returned its investors' initial capital (a 1x return) was considered a top-quartile performer. This historical benchmark puts the scale of that market collapse and the subsequent struggle for VCs into stark perspective.
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.
Underperforming VC firms persist because the 7-10+ year feedback loop for returns allows them to raise multiple funds before performance is clear. Additionally, most LPs struggle to distinguish between a manager's true investment skill and market-driven luck.
A true bubble, like the dot-com crash, involves stock prices falling over 50% and staying depressed for years, with capital infusion dropping similarly. Short-term market corrections don't meet this historical definition. The current AI boom, despite frothiness, doesn't exhibit these signs yet.
The S&P 500's high concentration in 10 stocks is historically rare, seen only during the 'Nifty Fifty' and dot-com bubbles. In both prior cases, investors who bought at the peak waited 15 years to break even, highlighting the significant 'dead capital' risk in today's market.
To truly understand an investment's resilience, analyze its performance over a 20-year span, paying close attention to how it navigated major downturns like the dot-com bubble and the 2008 financial crisis. This deep historical analysis provides a clearer picture of stability than recent performance alone.
The standard VC heuristic—that each investment must potentially return the entire fund—is strained by hyper-valuations. For a company raising at ~$200M, a typical fund needs a 60x return, meaning a $12 billion exit is the minimum for the investment to be a success, not a grand slam.
Botha argues venture capital isn't a scalable asset class. Despite massive capital inflows (~$250B/year), the number of significant ($1B+) exits hasn't increased from ~20 per year. The math for industry-wide returns doesn't work, making it a "return-free risk" for many LPs.
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.
The venture capital return model has shifted so dramatically that even some multi-billion-dollar exits are insufficient. This forces VCs to screen for 'immortal' founders capable of building $10B+ companies from inception, making traditionally solid businesses run by 'mortal founders' increasingly uninvestable by top funds.
The majority of venture capital funds fail to return capital, with a 60% loss-making base rate. This highlights that VC is a power-law-driven asset class. The key to success is not picking consistently good funds, but ensuring access to the tiny fraction of funds that generate extraordinary, outlier returns.