6 Levels of AI Investing Everyone Should Know
Lonsdale, Moshkovich, and Kolicich break down AI investing through a six-level framework spanning from energy infrastructure to end-user applications, arguing that while LLM companies command massive valuations, many are becoming commoditized in certain domains. The hosts challenge the conventional wisdom about AI model valuations by examining how different companies (OpenAI, Anthropic, Google, Meta, and X) are positioning themselves around distinct data assets and business models rather than competing purely on model capability.
Key takeaways
- • The six-level AI stack progresses from energy → chips → data centers → LLMs → software infrastructure → applications, with the most defensible value often concentrated at Level 5 (applications) rather than in the model companies themselves.
- • AI models exhibit commodity-like characteristics in certain use cases (document processing, structured output) where open-source alternatives work well, while remaining premium in frontier domains like coding and reasoning where proprietary models command pricing power.
- • Current LLM company margins (50-60% on APIs) far exceed true commodity businesses (5-15%), but the critical question is whether this durability persists as capabilities commoditize—a timeline dependent on how quickly rivals catch up.
- • Model companies' defensibility will depend less on raw capability and more on building product moats and data gravity (memory systems that lock in customers through personalization), similar to how AWS moved beyond commoditized compute primitives into managed services.
- • Different AI labs pursue divergent business models: OpenAI focuses on consumer, Anthropic on developer infrastructure, Google on productivity suite integration, Meta on content/culture, and X/Grok on reasoning and physical-world robotics—making them less direct competitors than ecosystem players.
- • Investor incentives heavily bias narrative around AI valuations—those with billions deployed want models to remain scarce and valuable, while infrastructure players benefit from positioning them as commodities, creating systematic bias in public discourse.
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