Innovators
1 Curated Dialogues
Sam Lessin
Key Views & Dialogues
20VC: Is Chamath Right: Is DPI The Only Thing That Matters | Does OpenAI Even Matter | Mary Meekers AI Report: The Analysis| IPO Breakdown: Chime, Circle & Thoma Bravo’s New Fund
DPI ultimately proves whether a venture fund made money, but TVPI remains a noisy early signal as venture splits between small funds with entry-price leverage and mega-funds able to overwhelm late rounds. AI’s 99.7% token-cost decline, $212bn of Big Six CapEx and agents abstracting SaaS interfaces create both infrastructure demand and an unresolved risk: OpenAI could miss projections by about 40% if it is merely “as good as Google.”
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- DPI ultimately settles whether a venture fund made money, but TVPI remains a noisy early signal rather than “nothing.” Sam Lessin backs Chamath’s “you can only eat net DPI” line and separates investors from fee-driven asset gatherers; Rory counters that a three-to-four-year 2.0x TVPI fund probably contains more information than one at 0.8x. Sam’s practical compromise: early on, show him “five names that matter”; later, return cash.
- Venture is splitting between small funds with entry-price leverage and mega-funds able to overwhelm late rounds, leaving roughly $200 million-to-$1 billion vehicles under pressure. Sam calls $1 billion “the death zone,” while Rory argues a $900 million fund can still work with about 30 investments and $20 million-$30 million checks. The genuine danger is ownership: when a normal Series A consumes $20 million-$30 million and giant funds can deploy at almost any price, mid-sized managers need exceptional selection and pricing discipline.
- Selling winners is a separate skill from finding them, and the right answer depends on whether an investment still has “infinity” potential. Sam’s first rule is “you cannot sell the things that matter,” but once the thesis breaks—as it did for him in Allbirds and Astra—available liquidity should be taken. Chime crystallizes the dispute: selling at its prior $25 billion valuation looks smart against an approximately $14 billion market cap, yet a later speaker notes that selling Revolut at $25 billion could miss a path to $100 billion-$150 billion.
- The panel’s sharpest disagreement is over whether merely good companies matter when only a handful become generational. Sam says OpenAI “might matter” but that even its long-run importance remains unsettled; Harry and Jason push the logic through Box, asking whether Aaron Levie therefore wasted 16 years building a roughly $5.5 billion company. Rory accepts he may never back a $100 billion outcome, yet rejects the resulting nihilism: $5 billion-$10 billion businesses and an $80 million carry check remain real value.
- AI demand is historic, but expectations and infrastructure commitments leave almost no tolerance for an ordinary outcome. ChatGPT reached 800 million users in 17 months, while the Big Six spent $212 billion on CapEx and Sam frames a roughly $600 billion CapEx business. Rory’s warning is that if OpenAI proves merely “as good as Google” on the comparable growth curve, it could miss next year’s projection by about 40%—a fundamentally great result that markets could still treat as failure.
- Falling inference costs and Chinese competition undermine any thesis built on scarce, expensive intelligence. Mary Meeker’s report puts token-cost compression at 99.7% in two years; DeepSeek reportedly reached 93% of o3-mini’s performance for a fraction of the cost, while Baidu ERNIE was cited at 0.2% of GPT-4.5’s cost. Sam’s call is categorical: “The price of a unit of intelligence is plummeting every month,” so teams should build for capabilities and economics likely to exist by launch.
- The immediate SaaS risk is organizational inertia, followed by agents and MCP erasing the application interface. Jason calls cautious pilots the “AI slow roll” and says startups need “existential dread”; Sam expects systems of work to capture value from systems of record that increasingly become invisible databases. Mangomint’s CEO supplied the concrete warning: if ChatGPT can choose and book a spa without exposing its scheduling software, the SaaS vendor can “become a pipe overnight.”
- Liquidity is returning, but price and ownership determine who benefits. Thoma Bravo raised a record fund of roughly $34 billion-$35 billion after distributing $30 billion, normal IPOs are resuming, and Snowflake and Databricks paid roughly $250 million for Crunchy Data and $1 billion for Neon as AI blurs data-platform boundaries. Meanwhile, YC AI companies are being pushed toward $50 million-$60 million post-money valuations; that is excellent financing for founders, but a venture fund ending with 3% ownership must be dramatically better at picking.