An analysis of 547 Series B deals reveals two-thirds return less than 2x. This data demonstrates that a "spray and pray" strategy fails at this stage. The cost of misses is too high, and being even slightly worse than average in your picks will result in a failed fund. Discipline and picking are paramount.
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.
Backing independent sponsors on a deal-by-deal basis is more than an investment strategy; it is an extended due diligence process. This approach provides deep, real-time insights into a manager's problem-solving skills under pressure, offering transparency that is impossible to achieve before a Fund I commitment.
A common mistake for emerging managers is pitching LPs solely on the potential for huge returns. Institutional LPs are often more concerned with how a fund's specific strategy, size, and focus align with their overall portfolio construction. Demonstrating a clear, disciplined strategy is more compelling than promising an 8x return.
The current fundraising environment is the most binary in recent memory. Startups with the "right" narrative—AI-native, elite incubator pedigree, explosive growth—get funded easily. Companies with solid but non-hype metrics, like classic SaaS growers, are finding it nearly impossible to raise capital. The middle market has vanished.
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.
When making early-stage investments, avoid the common pitfall of betting on just a great idea or just a great founder. A successful investment requires deep belief in both. Every time the speaker has invested with only one of the two criteria met, they have lost money. The mandate must be 'two for two.'
Acknowledging venture capital's power-law returns makes winner-picking nearly impossible. Vested's quantitative model doesn't try. Instead, it identifies the top quintile of all startups to create a high-potential "pond." The strategy is then to achieve broad diversification within this pre-qualified group, ensuring they capture the eventual outliers.
An entrepreneur's success rate dramatically shifted from 0 for 12 to 5 for 5 not because his execution improved, but because his project selection did. He stopped chasing high-risk, "one in a million" moonshots (like building the next social network) and focused on businesses with clearer paths to revenue (e-commerce, services).
This provides a simple but powerful framework for venture investing. For companies in markets with demonstrably huge TAMs (e.g., AI coding), valuation is secondary to backing the winner. For markets with a more uncertain or constrained TAM (e.g., vertical SaaS), traditional valuation discipline and entry price matter significantly.
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.