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

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch · November 7, 2026

5 Selected Lessons:

heuristic · 2 case · 1 framework · 1 reasoning_pattern · 1

Proactive, offensive deal sourcing instead of waiting on IR/syndication calls

framework based on: lived experience Scott Wilson

Source

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch — 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 (November 7, 2026) · at 22:36 ▸ · at 25:37 ▸

When this applies

when deciding whether to passively wait for partners/vendors to bring opportunities, or to actively go out and identify the best ones yourself

The takeaway

Waiting passively for a counterparty to offer you an opportunity selects for what they're willing to share, which systematically differs from (and is often worse than) what's actually best.

Why it works

Deals proactively surfaced by the LP (asking managers directly which portfolio companies they're most excited about) avoid the negative selection bias inherent in deals a manager chooses to syndicate out, which are often the ones the manager is less excited to hold alone.

One level up

Whoever controls the selection of what gets offered to you controls the quality of your opportunity set — go find the best yourself rather than relying on what's pushed to you.

Where it stops holding

This stops working when the sourcing organization lacks the relationships, staff time, or credibility to get candid answers directly from partners about their best ideas.

Detail

procedure:

Ask fund partners directly which 5 portfolio companies they are most excited about
Go meet those companies directly rather than waiting for a syndication offer
If interested, proactively ask to help lead the next round, get on the cap table, or run employee tender offers

benchmarks: {"biggest_takeaway":"WashU has done much better on this offensive outbound strategy than on defensive, inbound co-investment opportunities"}

rationale: Inbound syndication deals (e.g., 'we have $500M of OpenAI to syndicate') carry negative selection bias — they're offered precisely because the manager wants to share the risk/excess allocation, not because they're the best opportunities.

China investing: judging political risk by comparing actual observed behavior, not headline fear

reasoning_pattern based on: lived experience Scott Wilson

Source

When this applies

when deciding whether to enter a market widely perceived as too politically risky, despite consensus avoidance

The takeaway

Benchmark a market's political/regulatory risk against actual comparable incidents in 'safe' markets, not against its reputation, before writing off an entire geography.

Why it works

Comparing actual observed expropriation-like behavior across jurisdictions (e.g., UK/Norway windfall tax hikes vs. China) reveals that perceived political risk is sometimes higher in visibility than in actual severity, while 'developed market' risk is underweighted by comparison.

One level up

Visibility/salience of risk (what gets talked about) is not the same as magnitude of risk (what actually happens) — investors should separate the two.

Where it stops holding

This stops working when the feared risk, even if historically rare, carries catastrophic/irreversible downside (e.g., total expropriation or capital lockup) that isn't offset by any amount of favorable base-rate comparison.

Detail

approach: When assessing geopolitical/regulatory risk in a market, look for concrete historical analogs of adverse government action in both the 'risky' and 'safe' markets to calibrate true relative risk.

signals:

government actions that functionally confiscate large portions of company value (e.g., tax rate from 25% to 75%)
comparing frequency/severity of such actions across jurisdictions
distinguishing companies that are pragmatic and return capital to shareholders from those more exposed to state intervention

rationale: I've never seen that behavior in China [confiscatory-level tax hikes]... they more or less did the same thing in Norway and the UK — suggesting developed-market political risk can rival or exceed China's in specific instances.

In their words

Well, you see that, but like we, you know, we've seen worse behavior on very developed markets, like in the UK, where there was like offshore, like in the northern part of the UK, where they had offshore oil and whatever energy assets. And they took the tax rate from 25% to 75%.

spoken at 48:15 ▸

Public vs private allocation driven by liquidity need, not asset-class purity

heuristic based on: lived experience Scott Wilson

Source

When this applies

when allocating capital between liquid and illiquid asset classes under a payout/withdrawal obligation

The takeaway

Your tolerance for illiquid, higher-return assets is set by your mandatory cash outflow needs, not by a belief about which asset class is 'better.'

Why it works

Required payouts must come from liquid assets; private portfolios can't be reliably converted to cash on demand, so payout obligations mechanically cap how illiquid you can be.

One level up

Structure capital allocation around real constraints (liquidity, obligations) first; let return beliefs operate within that envelope.

Where it stops holding

This stops working when there is no mandatory payout/outflow constraint, in which case allocation can shift freely toward the higher-expected-return asset class.

Detail

rule: Target private allocation is capped by the fraction of liquid assets needed to fund payouts; absent the payout obligation, allocate much more aggressively to privates.

threshold: With 5% payout and half the portfolio liquid, that's effectively 10% of the liquid portfolio paid out yearly; without any payout, WashU would target 70-80% privates vs. the current ~50/50.

rationale: Privates compounded in the low-to-mid 20s vs ~10% for public equities over the last decade, per Wilson, but payout obligations constrain how much of the real liquid need can be met from an uncertain-liquidity private book.

In their words

Yeah, I mean, well, your payout is a function of your liquid assets, right? Because you can't always convert your private portfolio into the payout is not guaranteed, right?

spoken at 7:41 ▸

Concentration limits are mostly artificial

heuristic based on: lived experience Scott Wilson

Source

When this applies

when any portfolio-construction rule imposes a rigid cap on position size regardless of conviction or portfolio-level impact

The takeaway

Judge concentration risk at the level of your total portfolio, not at the level of an individual vehicle's internal percentage.

Why it works

A rigid percentage cap ignores the actual portfolio-level impact of the position; a concentrated bet inside a small fund can still be tiny relative to the whole LP portfolio, so the cap destroys upside without reducing real portfolio risk.

One level up

Rules of thumb that are context-blind (ignoring the larger system) create artificial constraints that dampen legitimate high-conviction upside.

Where it stops holding

This stops working when the LP/investor genuinely has only one exposure to that position (no diversification elsewhere), making the cap a real risk control rather than an artificial one.

Detail

rule: A 10% single-name concentration limit inside a fund is often meaningless at the LP portfolio level if that fund itself is a small fraction of the LP's total capital.

threshold: If a fund is only 1-2% of the LP's total portfolio, even a 50% position within that fund is only 50-100bps of the LP's overall book — an acceptable concentration.

rationale: WashU holds SpaceX-like positions (once >20% of the portfolio) through continuation vehicles, requiring board approval above 2-4% at cost, showing real concentration is managed via governance, not blanket fund-level caps.

In their words

I do. They're mostly artificial. You know, if you think over the course of like, say, you're going to do five funds, that's X amount of capital. And to have a 10% concentration limit in any individual fund, I don't think it makes sense.

spoken at 13:17 ▸

Direct/co-investment program as the real alpha source

case based on: data cited Scott Wilson

Source

When this applies

when deciding whether to build in-house execution capability versus relying solely on intermediaries/vendors

The takeaway

If you want outperformance beyond what your intermediaries already deliver, you must build and staff genuine first-hand evaluation capability, not just pick better intermediaries.

Why it works

Direct investing requires dedicated time allocation (80-90% of team time meeting companies) and an internal underwriting muscle; without it, performance reverts to the peer average because fund selection alone doesn't differentiate.

One level up

Returns above the field's average usually require doing something structurally different in resource allocation, not just better judgment within the same structure.

Where it stops holding

This stops working when the organization lacks the time, headcount, or skill to independently underwrite opportunities — in which case building a token direct program without real capability won't move performance.

Detail

situation: Most peer LPs spend 70-90% of time with fund managers and only ~10% with direct companies.

decision: WashU inverted this, spending 80-90% of team time meeting individual companies directly, using fund managers' highest-conviction picks as a starting filter ('starting on second or third base').

outcome: Without direct/co-investments, WashU's return would have been average for its peer group; with them, it's at or near the top of the peer group over the last decade.

lesson: Fund selection skill alone wasn't differentiating; the direct-investing muscle was the source of outperformance.

In their words

But if you look at our performance over the last decade, if we didn't have any direct or co-investments, we would have been right at the average of our peer group. You know, as it is, I think we're at the top, if not the very top, of our peer group over the last decade.

spoken at 10:43 ▸