About this episode
How well do venture capital returns really reflect skill versus structure?
In this episode, David Weisburd speaks with Abe about what large-scale AngelList data reveals about seed investing, power-law returns, and why traditional assumptions around expected value, conviction, and diversification often break down. Abe explains how adverse selection shapes outcomes, why access matters more than insight, and where data-driven strategies may — and may not — apply in venture capital.
Highlights:
Why venture capital behaves differently across seed, Series A, and later stages
How power-law dynamics challenge the idea of expected value
The role of adverse selection in early-stage investing
Why diversification can outperform concentrated conviction at seed
What AngelList data reveals about pricing, dilution, and markups
Why small checks often outperform large checks
The limits of quantitative models in startup selection
How common signals outweigh idiosyncratic insight
Using data to evaluate venture fund managers rather than startups
Guest Bio:
Abe is a consulting researcher at AngelList and CIO of Strawberry Tree Management Company which recently got renamed to AngelList Asset Management LLC, an independent RIA affiliated with AngelList. He works with large-scale venture data to study early-stage investing behavior, power-law returns, and fund performance, with a focus on understanding how structure, pricing, and access influence outcomes across the venture ecosystem.
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Sponsor:
AlphaSense is the AI-powered market intelligence platform trusted by 85% of the S&P 100, helping investment professionals make faster, more confident, data-driven decisions. Built for hedge funds, asset allocators, private venture capital firms, and investment bankers, AlphaSense uses advanced AI and powerful search across premium proprietary content to surface the insights that matter most—before the market moves. Elevate your research and stay ahead of the competition. Visit https://www.alpha-sense.com/howiinvest/ to learn more.
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