Patrick O'Shaughnessy

Patrick O'Shaughnessy × Michael Moritz

The structural edge that enabled Moritz’s venture career—pre-internet imperfect information, close founder relationships, and few competitors—dissipated “maybe 15, 16 years ago,” leaving today’s ecosystem healthy “if you’re a founder.”His Sequoia discipline tied compensation to performance, while he sees AI creating more jobs than it loses and tool-armed founders expanding what small companies can accomplish, with disruption across particular sectors still certain.

Patrick O'Shaughnessy × Sarah Guo

Sarah Guo says competitive open-source AI is already widespread, so US restrictions could handicap law-abiding American businesses while adversaries ignore them.Her roughly 250-person network sees recursive self-improvement and “some sort of exponential intelligence” as a one-to-two-year possibility, while Sunday Robotics targets home-robot beta by year-end.Compute independence, regulation, and physical supply chains remain constraints, while Chai Discovery’s $10 million contract and customer adoption test AI’s ability to capture value in biology.

Patrick O'Shaughnessy × Eric Vishria

AI is likely to produce an oligopoly plus $100B specialists, not a single winner-take-all lab, while Fireworks shows inference’s hidden moat: roughly 5X speed and multiple-X throughput on the same models and NVIDIA hardware.SaaS incumbents now face “Get to AI or be worth three times revenue,” as migration becomes easier and cost, iteration speed, and transportability matter more, with energy—especially China’s roughly tenfold buildout next year—the key constraint.

Patrick O'Shaughnessy × Jeremy Giffon

Giffon argues that capital follows the “billion-dollar PDF”: in long-dated private markets, narrative is the great filter, while X’s unifeed increasingly selects the stories that move marginal security prices.AI shifts software economics from near-zero-cost strings to recurring compute, implying lower margins and greater scale; Giffon has largely sat out the jump ball, while LPs should underwrite manager incentives and the increasingly extractive SPV structure.

Patrick O'Shaughnessy × Alex Sacerdote

Anthropic’s agentic coding release helped reverse Whale Rock’s view, supporting its August 2025 investment at the $180 valuation after it passed on the $60B round.Enterprise AI is less than 1% penetrated, yet Anthropic has only half the compute it needs, while a three-horse model oligopoly and infrastructure bottlenecks support monitoring adoption, supply, and the risk that open source catches up.

Patrick O'Shaughnessy × Gavin Baker

Anthropic added $11B of ARR in March while tech reached its cheapest relative valuation in 10 years, making the drawdown a differentiated demand signal rather than a capitulation event.At a rumored $900B on $50B ARR, Baker estimates unconstrained run-rate revenue of $100–200B, while TSMC’s capacity choices remain the key bubble test and orbital compute threatens terrestrial power-and-cooling ramps.

Patrick O'Shaughnessy × Gavin Baker

Anthropic added $11 billion of ARR in one month, while Asian AWS prices doubled, GPU availability fell, and DRAM went vertical as reasoning increased inference demand.Baker sees compute-constrained revenue upside, but TSMC capacity remains the key test for whether AI becomes an infrastructure bubble.

Patrick O'Shaughnessy × Mitchell Green

Mitchell Green sees public software as a potential risk-adjusted opportunity because distribution, customer success, and switching costs still protect incumbents such as Workday despite AI disruption fears.He expects the AI capex bubble to end badly as models commoditize, with the eventual drawdown creating an entry point, while Lead Edge’s sell discipline and 70% special-situations allocation offer nearer-term liquidity advantages.

Patrick O'Shaughnessy × Dan Sundheim

Dan Sundheim sees a moment-in-time opportunity in late-stage privates, where some of the largest companies by market cap remain private, and AI-lab investments inform public-equity analysis.The LLM debate now centers on unprecedented capital intensity: four or five models may endure, while hyperscalers could grow faster yet worsen as labs potentially insource compute in 5-10 years; software, scaling laws, and training returns remain watchpoints.

Patrick O'Shaughnessy × Josh Kushner

Thrive’s concentrated bets in Stripe at $50B and OpenAI reflect a long-term conviction that value will concentrate in fewer, much larger private and public companies.Its three-bucket strategy spans AI-native leaders, enabling infrastructure and permanent-capital Holdings, while the unresolved risk is that AI’s paradigm shift will also produce substantial capital loss.