Truthmark for AI Loop Engineering: Keeping Product Behavior Observable

AI coding agents are useful because they can make changes quickly. That same strength creates a review problem. In a typical loop, an agent edits code, runs tests, reads failures, patches the implementation, and repeats. The loop may finish with clean tests and a reasonable diff. But somewhere along the way, a small behavior can change: a timeout becomes longer, an optional field becomes required, a retry policy becomes more forgiving, or an API starts accepting a state that used to be rejected.