Invest Like The Best
Conversations with investors and business leaders about their ideas, methods, and stories related to investing time and money.
Coding Revenue and Compute Shortages Are Extending the AI Boom
Alex Sacerdote, founder and portfolio manager of Whale Rock Capital Management, argues that AI is still at the earliest stage of enterprise adoption and may be a steeper curve than prior technology shifts. In his telling, coding has become the first clear proof that AI can generate large revenue by replacing or augmenting labor, while the model layer is consolidating around a few leaders rather than commoditizing. Sacerdote’s broader case is that investors are underestimating both the earnings power of those winners and the hardware renaissance required to supply the compute behind them.
Uber’s Trillion-Dollar AV Bet Depends on Aggregating Autonomous Supply
Uber chief executive Dara Khosrowshahi argues that the company’s next phase depends on becoming the supply aggregator for “physical AI”: autonomous vehicles, drones, delivery networks, and other systems that turn digital demand into real-world services. In an Invest Like the Best interview, he says Uber’s advantage is not simply consumer demand but access to drivers, merchants, couriers, fleets, and eventually autonomous supply — a position he believes could open another trillion-dollar marketplace if lower costs and higher reliability expand usage.
AI Has Made Technology Fluency Mandatory for Fundamental Investors
Dan Loeb, founder of Third Point, argues that investing has become inseparable from technology, with AI, semiconductors and energy now overriding much of the usual macro framework. In a conversation with Patrick O’Shaughnessy, Loeb traces Third Point’s shift from event-driven credit and deep-value situations toward quality businesses, thematic technology investing, activism and cross-capital-structure credit, while maintaining that markets still misprice companies because humans, governance failures and structural trading constraints have not gone away.
The U.S. Military’s Constraint Is Industrial Depth, Not Battlefield Skill
Former Pentagon official Darren Farber argues to Patrick O’Shaughnessy that the United States’ military advantage depends less on battlefield skill than on whether its politics, industrial base, and technology pipeline can sustain force before a crisis becomes existential. Farber portrays China and Iran as powerful but brittle authoritarian systems, while warning that democracies face a harder test: defining victory, maintaining public consent, and converting commercial innovation into usable military depth. His case links Ukraine’s drone war, Taiwan, the Strait of Hormuz, defense startups, and military AI to a single constraint — whether America can turn legitimacy and markets into durable strategic capacity.
TSMC’s Wafer Scarcity May Be Preventing an AI Overbuild
Investor Gavin Baker argues on Invest Like The Best that the AI boom is being organized less by software adoption than by scarcity: compute demand is outrunning power, wafers, and frontier-model access. In his account, Anthropic’s growth, Nvidia’s position, TSMC’s capacity discipline, and even SpaceX’s possible orbital compute are all expressions of the same constraint. Baker’s central claim is that the AI cycle may avoid a classic infrastructure bubble only if physical bottlenecks, especially leading-edge wafer supply, keep capital from building far ahead of demand.
Compute Allocation Is Anthropic’s Core Constraint as Claude Revenue Surges
Anthropic CFO Krishna Rao argues that the company’s rise is best understood through compute: a scarce capital asset that must be bought years ahead and constantly reallocated across model training, customer demand, internal automation and future products. In an interview with Patrick O’Shaughnessy, Rao says ordinary forecasting and software-margin frameworks break down when model capability, adoption and revenue compound together, leaving Anthropic to manage growth through scenarios rather than point estimates.
Airbnb Is Rebuilding Around Identity, Not Homes, for AI
Airbnb’s challenge in the AI era is less a feature rollout than a company reinvention, chief executive Brian Chesky argues in a conversation with Patrick O’Shaughnessy. Chesky says the company has to move beyond a business still identified mainly with homes, rebuild around identity and personal preferences, and do so without damaging a large public platform that hosts and investors depend on. His answer is a more hands-on operating model: fewer abstraction layers, smaller elite teams closer to users, continuous recruiting, and a CEO directly engaged with the work.