The primary area of innovation is shifting from base models to the "harnesses"—the applications and SDKs that make models useful. Products like Cursor and OpenAI's Codex are becoming crucial differentiators by focusing on user experience and workflow integration. The application layer, not the model layer, may now determine market leadership.

Foundational AI models will commoditize into a utility layer where companies buy "intelligence on the fly." The real, sustainable profit will be captured by application companies that leverage various models to solve specific business problems, as most enterprises lack the expertise to use raw models effectively.

As foundational AI models become more accessible, the key to winning the market is shifting from having the most advanced model to creating the best user experience. This "age of productization" means skilled product managers who can effectively package AI capabilities are becoming as crucial as the researchers themselves.

The frontier of AI competition is moving beyond raw model performance (e.g., Opus vs. GPT). The new battleground is the ecosystem of agentic 'harnesses'—specialized tools, workflows, and infrastructure—built around models. Anthropic's developer day focused entirely on these applications, signaling a major shift in where value is created.

The AI value stack has evolved from chips (NVIDIA) to models (OpenAI). The next critical phase is the application layer. It's unclear if value will be captured by new application companies or if the underlying model providers will absorb all the profits, a key question for investors and founders.

Maverick Capital predicts the AI value chain, which shifted from software to hardware, will swing back. Value will move from upstream bottlenecks (fabrication, materials) downstream to the application/infrastructure layer as AI agents integrate with existing enterprise workflows rather than replacing them.

AI companies are pivoting from simply building more powerful models to creating downstream applications. This shift is driven by the fact that enterprises, despite investing heavily in AI promises, have largely failed to see financial returns. The focus is now on customized, problem-first solutions to deliver tangible value.

The assumption that building the most advanced AI model creates a defensible, high-margin business is collapsing. With competitors offering comparable performance at lower prices, the sustainable advantage shifts from owning the best intelligence to how that intelligence is productized and integrated.

The economic value in AI is rapidly shifting away from foundational models, which are becoming commoditized far faster than anticipated. The real, sustainable business models are emerging at the infrastructure layer (cloud, chips) and the application layer, not in the foundational models themselves.