Why AI Doesn't Code What You Designed: The Structural Gap Between Specs and Implementation

You write a detailed design doc. You paste it into your AI assistant. You wait. The output compiles. Tests pass. And yet — it's not quite what you designed. The auth middleware is in the wrong layer. The error handling pattern differs from the rest of the codebase. The field names don't match the schema. You fix it. Next task, same thing. This happens constantly, and it's not a model capability problem. It's a structural problem in how we communicate design intent to AI. And "write better prompt