Ten talks. Ten practitioners from different companies — Anthropic, Google, HashiCorp, Thoughtworks, Answer.AI, Factory, and independent creators. None of them coordinated. All of them arrived at the same conclusion.

Clean code isn’t a nice-to-have in the age of agents. It’s infrastructure.

I spent the last few weeks watching the Pragmatic Engineer podcast series on AI-assisted software engineering, plus Jeremy Howard’s deep dive on Machine Learning Street Talk and Eno Reyes’s talk at the AI Engineer Summit. These aren’t pundits speculating about the future — they’re builders shipping production software with AI agents every day. And the pattern that emerges across all of them is striking: the bottleneck for agent productivity isn’t model capability. It’s the codebase the model has to work with.