David George of Andreessen Horowitz reveals that contrary to the belief that smaller funds yield higher multiples, a16z's best-performing fund is a $1B vehicle. This success is driven by capturing enough ownership in massive winners like Databricks and Coinbase, demonstrating that fund size can be an advantage in today's market where value creation extends into later private stages.
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Contrary to the 'get in early' mantra, the certainty of a 3-5x return on a category-defining company like Databricks can be a more attractive investment than a high-risk seed deal. The time and risk-adjusted returns for late-stage winners are often superior.
Mega-funds can justify paying "stupid prices" at the seed stage because they aren't underwriting a seed-stage return. Instead, they are buying an option on the next, much larger round where they'll deploy real capital. This allows them to outbid smaller funds who need to generate returns from the initial investment itself.
Thrive's data shows the number of companies reaching $100B+ valuation grew faster last decade than those reaching $10B. This suggests it's a higher-probability bet to identify future mega-winners from an established pool of large companies than to pick breakout unicorns from a much larger, riskier field of thousands.
The venture capital industry was transformed by two parallel forces post-financial crisis. Crossover funds brought a hedge fund-style intensity and speed, while founder-led firms like a16z brought an entrepreneurial metabolism. This dual injection of urgency permanently changed the pace and nature of venture investing.
Contrary to the instinct to sell a big winner, top fund managers often hold onto their best-performing companies. The initial 10x return is a strong signal of a best-in-class product, team, and market, indicating potential for continued exponential growth rather than a peak.
Applying Conway's Law to venture, a firm's strategy is dictated by its fund size and team structure. A $7B fund must participate in mega-rounds to deploy capital effectively, while a smaller fund like Benchmark is structured to pursue astronomical money-on-money returns from earlier stages, making mega-deals strategically illogical.
The primary risk to a VC fund's performance isn't its absolute size but rather a dramatic increase (e.g., doubling) from one fund to the next. This forces firms to change their strategy and write larger checks than their conviction muscle is built for.
A smaller fund size enables investments in seemingly niche but potentially lucrative sectors, such as software for dental labs. A larger fund would have to pass on such a deal, not because the founder is weak, but because the potential exit isn't large enough to satisfy their fund return model.
The firm targets markets structured like the famous movie scene: first place wins big, second gets little, and third fails. They believe most tech markets, even B2B SaaS without network effects, concentrate value in the #1 player, making leadership essential for outsized returns.
AI startups' explosive growth ($1M to $100M ARR in 2 years) will make venture's power law even more extreme. LPs may need a new evaluation model, underwriting VCs across "bundles of three funds" where they expect two modest performers (e.g., 1.5x) and one massive outlier (10x) to drive overall returns.
