Patrick O'Shaughnessy

Patrick O'Shaughnessy × Gabe Stengel

Rogo’s model-era progression—from o1 Pro’s reliable search to Opus 4.5 handling junior finance work—supports a two-year race to redesign investment firms, not wait for better models.Its wedge is private-market dealmaking, where data rooms, DDQs, CRM and LP reporting still lack infrastructure, while high-value ideas can justify extreme token spend.The watchpoints are compaction, standardization, and whether incumbents move aggressively enough.

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 × John Kim

John Kim frames fundraising as a trust problem: desire minus fear drives action, while returns alone miss the motivations of most LPs and committees rarely make contrarian bets.His operating rules are to anchor scale to the first close, simplify the story, choose two of size, speed and terms, and build pipeline through conversion and bite size without sacrificing the differentiation that created the franchise.

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 × Scott Nolan

America’s zero commercial uranium-enrichment capacity makes fuel the bottleneck for advanced nuclear power, with HALEU scarcity and the January 1, 2028 Russian-import ban creating defined market openings.General Matter targets dollars per kilogram-SWU as its cost metric, while data-center demand and behind-the-meter SMRs could accelerate deployment; execution, permitting, and the economics of nuclear construction remain key risks.