![Alex Sacerdote - How to Invest Through Technology Cycles - [Invest Like the Best, EP.477]](https://megaphone.imgix.net/podcasts/638034f8-63bb-11f1-8c95-6396d39926c0/image/bf350c0e87fc4d280ef1c0572526d26d.jpg?ixlib=rails-4.3.1&max-w=3000&max-h=3000&fit=crop&auto=format,compress)
Alex Sacerdote argues the AI foundational model space is narrowing to an oligopoly of OpenAI, Anthropic, and Google, much like the cloud market consolidated around AWS, Azure, and GCP. This structure creates durable, profitable businesses for the winners.
The ability for AI to autonomously write functional code from natural language, or "agentic coding," represents a massive market unlock. This specific application is a half-trillion-dollar opportunity that validates huge investments in AI models and infrastructure.
A powerful due diligence tactic for private companies is to interview customers of their closest public competitor. By asking Adyen's customers about Stripe, WhaleRock uncovered that the market was a "Coke and Pepsi" duopoly, giving them conviction to invest.
For decades, data center hardware was a commoditized, low-margin industry. The extreme performance requirements of AI are reversing this trend, forcing innovation and creating significant pricing power for suppliers of everything from servers and networking to liquid cooling and printed circuit boards.
The traditional SaaS "Rule of 40" (Growth + Margin) is insufficient for the AI era. A better heuristic to gauge a company's AI leadership is to combine the percentage of its sales derived from AI with its market share in that specific AI category.
According to Andy Grove's wisdom, strategic inflection points can't be identified through lagging data. Instead, look for qualitative, anecdotal evidence like a standing-room-only crowd at a tech conference for a new product, as this signals the beginning of massive corporate demand.
The firm sold and shorted its software holdings based on a key insight: CIOs are deprioritizing traditional SaaS. They are redirecting budgets towards foundational model tokens (e.g., from Anthropic) that offer a more immediate and compelling return on investment.
While AI threatens many software companies, those built on strong network effects (like Slack) could become even more vital. AI agents will need to use these platforms as tools to perform tasks, solidifying their position as the central hub of work.
To secure allocations in competitive private rounds, public market investors like WhaleRock create extensive, proprietary research decks (e.g., a 90-page analysis). This demonstrates deep understanding and value beyond capital, earning them a spot over other investors.
Unlike technologies requiring physical installation (like dishwashers), AI tools are immediately available through a browser. This eliminates adoption friction, creating a vertical "L-curve" of adoption rather than a gradual S-curve, starting from a tiny base of users.
The market struggles to price exponential growth, creating opportunities to buy dominant tech companies at low forward earnings multiples (e.g., Nvidia at 4x). An understanding of S-curve adoption reveals this underappreciated earnings power before the market catches on.
Significant alpha exists in mega-cap stocks because their prices are set by the slow-moving consensus of hundreds of generalist portfolio managers. Specialist investors can identify fundamental shifts (e.g., Google's AI potential) and profit before the broader market catches up.