AI Investor and CEO Rob May Discusses the Value of the Post-Model World Thesis

Rob May, an AI investor and CEO, has developed a new framework for evaluating technology called the "Post-Model World thesis." This theory posits that while AI models are important, their value is diminishing relative to the broader systems they support. May argues that AI models are becoming foundational components, rather than differentiators, in the systems they power.

In his Substack newsletter "Investing in AI," May describes the shift away from evaluating AI models alone to assessing the systems in which they operate. He likens this to the difference between buying a car (the system) and an engine (the model). To test this theory, May founded Neurometric, an automated token-engineering platform that helps users efficiently allocate their workload across multiple smaller models rather than a single large, potentially inflexible one.

May's approach involves "model fragmentation," where systems perform best using several smaller models rather than one large model. His company Neurometric is focused on testing this concept by examining whether using multiple small models is more efficient than relying on a single large one. As Neurometric updates processes such as MCP protocol standardization and model routing, May shares progress and developments in his book manuscript, providing readers with a comprehensive view of the current state of AI investing.

While May continues to write his upcoming book, 90% of which is human-written, the remaining 10% is from an AI-written chapter to demonstrate the current state of writing technology using large language models (LLMs). This hands-on approach allows May to stay updated on AI developments, a crucial aspect in an industry known for rapid innovation.

With an angel and venture capital (VC) track record spanning over 75 AI companies, May grounds his decisions in real-time theorizing, both in his investments and his leadership of Neurometric.

Looking ahead, May plans to continue refining his theories on model fragmentation through his writing and work with Neurometric. He also intends to deepen his public markets commentary alongside the publication of his book, solidifying his position as an active contributor to the field of AI and AI development.