The Real Bottleneck in AI Agents Is Not the Model

The AI agent demos look great. The agent navigates to a page, clicks a button, fills a form, extracts data. Clean, fluid, purposeful. Then you try to run the same task across fifty concurrent sessions, or against a site with a slightly different DOM than last week, and everything falls apart.

For a long time, the industry consensus was that this was a model problem. Make the LLM smarter and the agent gets more reliable. I spent enough time building browser automation infrastructure to know that view is wrong. The model is not the bottleneck. The execution substrate is.

This is the core insight that drove me to design a stateless browser execution layer for AI agents and what building it taught me about where agentic systems actually break.

The Substrate Problem Nobody Talks About

Here is what a typical AI browser agent does when it receives a task: it...

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