Alex Sacerdote - How to Invest Through Technology Cycles - [Invest Like the Best, EP.477]
Summary
Alex Sacerdote, founder of Whale Rock Capital Management, an investment firm managing over \$17 billion and compounding at roughly 44 percent annually, details his 20-year framework for investing through technology cycles, focusing on S-curves, durable competitive advantages, and underappreciated earnings power. He highlights Anthropic as his highest conviction position, using it to illustrate investment opportunities across the AI stack, from chips to foundational models and applications. Sacerdote notes the foundational model layer has evolved into an oligopoly, with Anthropic, OpenAI, and Google as key players, and emphasizes Anthropic's enterprise focus and impact on the \$0.5 trillion coding market. He describes the "L-curve" growth of enterprise AI, currently less than 1% penetrated, and the "hardware renaissance" driven by AI's 10x annual workload growth, leading to decommoditization and innovation in components like high-bandwidth memory, ethernet switches, and PCBs. He also discusses Whale Rock's strategy for private market investments and the risks to the AI bull case.
Key takeaway
For investors navigating the current AI technology cycle, you should prioritize identifying S-curves in foundational models and the hardware renaissance. Focus on companies with durable competitive advantages and underappreciated long-term earnings power, like those in specialized chips and infrastructure. Be cautious with traditional enterprise software, as AI-native solutions and budget shifts pose significant disruption risks, potentially relegating incumbents to database roles.
Key insights
Investing in technology S-curves requires identifying competitive advantages and underappreciated earnings power, particularly in the evolving AI stack.
Principles
- Technology adoption follows S-curves, with exponential growth post-barrier removal.
- Digital competitive advantages (network effects, scale, IP) are highly durable.
- Underappreciated long-term earnings power fuels exponential investment returns.
Method
Identify new compute paradigms, deep dive into S-curves, study competitive advantages, and model underappreciated earnings power, using intuition at inflection points.
In practice
- Prioritize chips and infrastructure early in new compute paradigms.
- Monitor enterprise AI penetration for "L-curve" growth.
- Evaluate incumbent software for AI disruption and budget shifts.
Topics
- Technology S-Curves
- AI Investment Strategy
- Foundational Models
- AI Hardware
- Competitive Advantage
- Private Market Investing
- Enterprise Software Disruption
Best for: Investor, Director of AI/ML, Executive
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Editorial summary, takeaway, and curation by AIssential. Original article published by Invest Like the Best with Patrick O'Shaughnessy.