VCs often pass on great deals by overweighting the fear of future competition from giants like Google. The better mental model is to invest in founders with demonstrable "strength of strengths," accepting that some weaknesses are okay, rather than seeking a flawless profile.
A core part of a16z's growth fund strategy is to invest in companies the firm's early-stage team passed on. This acts as an internal "fix the mistake fund," providing a structured way to correct errors of omission and get a second chance at breakout companies.
The rationale behind backing Flow wasn't an oversight of past issues, but a deliberate strategy to invest in a founder with world-class, "spiking" strengths in brand building and company creation. This aligns with the firm's philosophy of prioritizing extreme strengths over a lack of weaknesses.
Counterintuitively, very high gross margins in a company pitching itself as "AI" can be a warning sign. It may indicate that users aren't engaging with the core, computationally expensive AI features. Lower margins can signal genuine, heavy usage of the core AI product.
Contrary to the belief that smaller VC funds generate higher multiples, a16z's data shows their larger funds can outperform. This is driven by the massive expansion of private markets, where significant value is now created in later growth stages (Series C and beyond).
As high-growth tech companies delay IPOs, the public small-cap market is left with lower-quality assets. The return on invested capital (ROIC) for the Russell 2500 index has more than halved over 30 years, signaling a fundamental shift for institutional investors.
The massive TAM expansion for AI relies on shifting spend from labor to technology budgets. This shift won't happen because of top-down CIO mandates. It must be driven by bottom-up product pull, where the value proposition is so overwhelmingly clear that customers are compelled to adopt it.
Since today's AI companies grow too fast to have multi-year renewal data, investors must adapt their diligence. The focus shifts from long-term retention to short-cycle retention and, crucially, deep product engagement. High usage is the best leading indicator of future stickiness and value.