Invest Like the Best

Patrick O'Shaughnessy × Ben Thompson

AI’s near-term bottleneck may be capital rather than compute or power, as funding shifts from free cash flow and debt toward Google equity and NVIDIA’s $500 billion vehicle.Thompson’s Berkshire analogy makes Search a possible funding engine for AI’s “basically all white-collar work” TAM, while payback periods, hyperscaler chips, and an air-gap risk remain watchpoints as 2028-29 capacity arrives.

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 × Gavin Baker

Gavin Baker argues that the AI selloff lacks a clear demand break: GPU rental prices, DRAM, tokens, and inference usage are accelerating, while open source shifts margins toward infrastructure rather than eliminating compute demand.Credit and regulation are the real catalysts to monitor, but expiring contracts could reprice installed GPUs sharply higher; Baker also sees SpaceX as an underappreciated compute platform, contingent on power, financing, and political acceptance.

Patrick O'Shaughnessy × Matthew Smith

Matthew Smith’s model points to US natural-gas storage falling below all historical levels by 2029 as contracted LNG and AI compute outstrip deliverability, with electricity prices bearing the impact in 2028-2030.The market remains priced near $3.50-3.60, while Expand Energy and Range offer leverage to a potential physical-gas scramble; processing, pipelines, nuclear timelines, and consumer costs remain key risks.

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 × Vlad Barbalat

Liberty Mutual’s $120B balance sheet combines roughly $70–75B of reserves with growth credit and equity, while permanent mutual capital avoids shareholder pressure and supports 7–10% portfolio targets.Barbalat now questions whether AI makes future cash flows—and therefore multiples—structurally less visible, with four-year software credit appearing safer than 30-year Salesforce or Oracle debt and potentially steeper credit curves ahead.

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 × Dan Loeb

Dan Loeb has reduced macro to oil and AI, making technology fluency essential as Jensen's stack reshapes power, chips, models, and applications.Third Point sees leading AI companies as the most attractive sector, while its fulcrum-security framework targets mispriced credit such as Twitter debt and xAI obligations.AI is also destabilizing traditional quality investing and forcing structural sellers, leaving governance, due diligence, and the durability of pricing power as key risks to monitor.

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 × Paul Tudor Jones

Paul Tudor Jones sees dollar-yen as an undervalued trade finally gaining a catalyst from Japan’s new leadership and its largely unhedged $4.5 trillion international investment position.He also flags a sovereign debt bubble and an IPO supply reversal as buybacks weaken under hyperscaler capex; the yen catalyst and 6–18-month unlock schedule remain key monitors.