E286: How LPs Can Actually Find Alpha in Venture

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Jan 20, 2026

Abe, a consulting researcher at AngelList and CIO of Strawberry Tree Management Company, dives deep into the dynamics of venture investing. He reveals how venture capital returns often misrepresent skill versus structure. Discover why seed stage investing requires broad exposure and how adverse selection plays a crucial role in outcomes. Abe shares insights on why small checks can outperform larger bets and how access, rather than mere insight, drives success in the venture ecosystem. His data-driven strategies challenge traditional assumptions, making for a compelling discussion on finding alpha in venture.

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INSIGHT

Price-Per-Share Reveals Real Returns

Access to true price-per-share and full seed outcomes removes survivorship bias and changes return estimates.
Public data and headline valuations mislead because they hide dilution and dead companies.

INSIGHT

Three Distinct Venture Asset Classes

Venture capital is three distinct asset classes: seed, Series A, and Series B+ behave very differently.
Power-law parameters change by stage, making seed uniquely extreme and later stages more like public markets.

ANECDOTE

Anthropic Example Of Low Dilution Winners

Anthropic raised a huge round with minimal dilution, illustrating winners both outperform and dilute less per-share.
AngelList's price-per-share data reveals those nuances that public headlines hide.

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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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Disclaimer:

This podcast is for informational purposes only and does not constitute investment, financial, legal, or tax advice. Nothing in this episode should be interpreted as an offer to buy or sell any securities or to participate in any investment strategy. All opinions expressed by the host and guests are their own and do not represent the views of Weisburd Capital. Participants may hold positions or have financial interests in the companies, funds, or investments discussed. Any references to specific investments are for illustrative purposes only. Investing involves risk, including the potential loss of capital. Past performance is not indicative of future results, and any forward-looking statements are subject to risks and uncertainties. Any third-party data or opinions have not been independently verified. Listeners should conduct their own research and consult their own advisors before making any investment decisions.

(0:00) Introduction (2:28) Insights from AngelList data and importance of share price (9:28) Investment strategies and market efficiency in early-stage investing (14:32) Power law distributions and their practical implications (20:15) Seed stage investing and LP perspectives (23:15) Quantum mechanics analogy and diligence strategies (27:36) Portfolio strategies and management fees impact (30:54) Specialized fund managers and adverse selection (37:08) Check sizes and signal in seed investing (42:15) Valuation, signal, and GP style drift (45:02) Strawberry Tree Management Company strategy (46:45) Quantitative GP selection and fund of funds approach (50:38) Pricing power and variability in VC funds (53:45) Broad investing in seed stage venture (55:35) Key signals and the role of DPI (58:12) Distinguishing skill from luck in early exits (1:00:05) Following Abe Othman’s work and advice from Mike Maples (1:01:50) Closing remarks