Most AI coding workflows still assume a simple pattern: give the model a prompt, let it write code, and then clean up whatever comes out. That can work for a small bug fix, a minor UI enhancement, or a narrow refactor. But once you are building real features in a complex production codebase, that model starts to break down.

The problem is not...