20VC: From $8BN to $19BN: Inside WashU's Endowment Fund | SpaceX Made Up 20% of Our AUM | Why Europe and China Has So Much Opportunity | The Reckoning That is Coming for AI Companies with Scott Wilson
Episode
58 min
Read time
2 min
Topics
Productivity, Investing, Fundraising & VC
AI-Generated Summary
Key Takeaways
- ✓Portfolio Concentration via Look-Through Positions: Target having 50% of total portfolio in the top 50 look-through company exposures, not fund exposures. Quantitative diversification benefits plateau beyond 30 underlying names. WashU tracks aggregate dollar exposure per company across all funds and direct investments, treating the portfolio as one unified book regardless of public or private status.
- ✓Offensive Co-Investment Strategy: Rather than waiting for fund managers to offer SPV allocations (which carry negative selection bias), proactively ask each manager for their five most-conviction portfolio companies, then independently meet those companies and pursue direct positions. This offensive approach, not fund selection alone, drove WashU's outperformance above peer-group averages over the past decade.
- ✓Avoid Adding Capital Based on Frame-of-Reference Bias: Wilson identifies his costliest mistake as refusing to add capital to high-conviction winners simply because valuations had risen from entry price. If a company remains the highest-conviction position in the portfolio, valuation increase alone is insufficient reason to stop compounding. This error cost WashU billions across multiple positions over nine years.
- ✓Private Market Valuation Reckoning: Late-stage private AI companies are priced at valuations the public markets will not validate at IPO, which explains the absence of DPI across the industry. Public markets are near all-time highs, so the bottleneck is not market access but the gap between private and public pricing. Roughly half of current AI model providers likely will not exist in ten years.
- ✓Smaller Funds Outperform on Capital Efficiency: A manager who raises $1B when they could raise $4B and returns every 18 months is preferable to a $10B fund returning every three years. In smaller funds, a single position can return the entire fund. Mega funds must either double check sizes at higher valuations or double the number of bets, both of which compress multiples of invested capital.
What It Covers
Scott Wilson, CIO of Washington University's endowment, explains how he grew the fund from $8B to nearly $20B by eliminating 36 hedge funds, concentrating positions in companies like SpaceX (once 20%+ of AUM), and spending 80-90% of team time meeting individual companies rather than fund managers.
Key Questions Answered
- •Portfolio Concentration via Look-Through Positions: Target having 50% of total portfolio in the top 50 look-through company exposures, not fund exposures. Quantitative diversification benefits plateau beyond 30 underlying names. WashU tracks aggregate dollar exposure per company across all funds and direct investments, treating the portfolio as one unified book regardless of public or private status.
- •Offensive Co-Investment Strategy: Rather than waiting for fund managers to offer SPV allocations (which carry negative selection bias), proactively ask each manager for their five most-conviction portfolio companies, then independently meet those companies and pursue direct positions. This offensive approach, not fund selection alone, drove WashU's outperformance above peer-group averages over the past decade.
- •Avoid Adding Capital Based on Frame-of-Reference Bias: Wilson identifies his costliest mistake as refusing to add capital to high-conviction winners simply because valuations had risen from entry price. If a company remains the highest-conviction position in the portfolio, valuation increase alone is insufficient reason to stop compounding. This error cost WashU billions across multiple positions over nine years.
- •Private Market Valuation Reckoning: Late-stage private AI companies are priced at valuations the public markets will not validate at IPO, which explains the absence of DPI across the industry. Public markets are near all-time highs, so the bottleneck is not market access but the gap between private and public pricing. Roughly half of current AI model providers likely will not exist in ten years.
- •Smaller Funds Outperform on Capital Efficiency: A manager who raises $1B when they could raise $4B and returns every 18 months is preferable to a $10B fund returning every three years. In smaller funds, a single position can return the entire fund. Mega funds must either double check sizes at higher valuations or double the number of bets, both of which compress multiples of invested capital.
Notable Moment
Wilson revealed that in 2020, WashU had a large block of LP interests ready for secondary sale at strong prices, but delayed to capture year-end markups. The market peaked shortly after, and the fund wrote down significant value — a decision Wilson describes as straightforward greed overriding clear judgment.
Episode Transcript
We had 36, 37 hedge funds in the portfolio. And when we got rid of them all, you know, 80, 90% of our time is just out meeting individual companies. And, and that's very different than probably how most of your LPs spend their time. You know, at one point north of 20% of the portfolio is in Space X. Half of our portfolio is in our top 50 look through positions. Our model doesn't really work with mega funds. They don't need our capital. We hardly ever talk about like fund performance. We we only really talk about the underlying exposures in the portfolio. Price is what you pay. Value is what you get. This is 20 VC with me, Harry Steppings. Now how often do you hear one of the biggest allocators in the world reveal how they make incredible investment decisions? Very rare. This CIO today has taken their institution from $8,000,000,000 to close to $20,000,000,000 today. I'm so excited to welcome an OG of the endowment fund space, Scott Wilson at WashU. Now the incredible fact about this institution is that at one point, SpaceX was over 20 of their portfolio. It has done incredibly well for them. And today, we discuss the journey from 8,000,000,000 to 20,000,000,000 in AUM. The biggest lessons, what they did that they wish they hadn't done, and what they didn't do that they wish they had done. This was an incredible show to do. But before we dive into the show today, today, I wanna tell you about how the first AI law firm, Crosby, helped us close a big sponsor. As you know, some of the biggest companies in the world advertise on 20. My British dulcet tones clearly convert well. I was working to close this big sponsor, and they wanted to get through legal review quite quickly to close the deal. Crosby turned red lines around in three hours and caught major issues that would have caused us serious problems in the future. Crosby combines AI, some of the best engineers in the world from companies like Ramp and Stripe, and some of the best attorneys in the world from top 10 law firms. Customers get the best of both worlds. An elite human attorney reviews every contract, but they move incredibly quickly, returning red lines in under four hours. They help the fastest growing companies like Cognition, Ramp, and Clay close deals in hours, not weeks. Learn more at crosby.ai/20vc. If you wanna redline NDAs, MSAs, DPAs, and any other procurement contracts faster, go to crosby.ai/20vc. It's speed that you can really trust. While Crosby keeps your numbers sharp, OneMind keeps your customer conversation sharper. Our friends over at OneMind have a hot take. The b to b GTM model we've been using for, well, the last twenty years, it's collapsing. Predictable revenue isn't so predictable, and buyers are just tired of explaining themselves at every handoff between SDRs, AEs, CSMs, and support. You feel it …
Get the full transcript (11,492 words) + summary by email — free
One-time email with the complete transcript and AI summary of this episode. No account needed.
One email, no spam. We’ll also show you what SignalCast does.
You just read a 3-minute summary of a 55-minute episode.
Get 20VC (20 Minute VC) summarized like this every Monday — plus up to 2 more podcasts, free.
Pick Your Podcasts — FreeKeep Reading
More from 20VC (20 Minute VC)
20VC: OpenAI Cuts Valuation to $1.25TRN | Public Market Meltdown: GOOG Loses $500BN in 12 Hours | DoorDash Buys Instacart for $17BN | Kalshi Raises $1BN and Cognition Eyes $80BN Valuation
Nov 5 · 69 min
a16z Podcast
Why a16z Launched the Machine Age Fund | Jen Kha
Aug 30
More from 20VC (20 Minute VC)
20VC: Who Wins the Inference Market | Has Open-Source LLM Inference Peaked? | What Happens to the Cost of Compute | The Real Limits of Post-Training and RL with Erik Bernhardsson, Modal CEO
Nov 2 · 62 min
The Prof G Pod
No Mercy / No Malice: ICE Age
Aug 8
More from 20VC (20 Minute VC)
We summarize every new episode. Want them in your inbox?
20VC: OpenAI Cuts Valuation to $1.25TRN | Public Market Meltdown: GOOG Loses $500BN in 12 Hours | DoorDash Buys Instacart for $17BN | Kalshi Raises $1BN and Cognition Eyes $80BN Valuation
20VC: Who Wins the Inference Market | Has Open-Source LLM Inference Peaked? | What Happens to the Cost of Compute | The Real Limits of Post-Training and RL with Erik Bernhardsson, Modal CEO
20VC: David Tisch on Why High Ownership and Concentration is BS | Why No Manager Actually Wants to Stay Small | Why Competing with the Mega Platforms is a Losing Game | Why the Lean Startup is a Fake?
20VC: Anthropic Files S1 Ahead of $2TRN IPO | Instinct's Rumoured $30 Billion Fundraise | Microsoft Laysoff 27,000 While Meta Taps Equity Markets for $95 Billion Capex Spending Spree
20VC: Satya Nadella on Open vs Closed Models: Who Wins | Whether to Trust Frontier Model Providers | Why Companies Need to Own Their Own Intelligence | The Importance of Verticalisation: From Chips to Models and More
Similar Episodes
Related episodes from other podcasts
a16z Podcast
Aug 30
Why a16z Launched the Machine Age Fund | Jen Kha
The Prof G Pod
Aug 8
No Mercy / No Malice: ICE Age
This Week in Startups
Jul 6
$100T is managed by “human duct tape” | E2308
Freakonomics Radio
Jun 26
679. Why Does Vanderbilt Keep Winning?
The Prof G Pod
Jun 24
Rebranding the Democratic Party + The College Affordability Crisis
Explore Related Topics
This podcast is featured in Best Investing Podcasts (2026) — ranked and reviewed with AI summaries.
Read this week's Investing & Markets Podcast Insights — cross-podcast analysis updated weekly.
You're clearly into 20VC (20 Minute VC).
Every Monday, we deliver AI summaries of the latest episodes from 20VC (20 Minute VC) and 192+ other podcasts. Free for one show.
Start My Monday DigestNo credit card · Unsubscribe anytime