AI coding agents ship features fast, but specs, tests, and code quietly drift apart. This guide covers a traceability model, spec-to-test and spec-to-code mapping, and the CI checks that catch drift before a merge.
A spec that nobody re-checks against the running system is worse than no spec at all, because it creates false confidence. Reviewers trust the document instead of the diff, and an AI agent asked to "follow the existing pattern" will happily follow whatever the code actually does, even when that contradicts the requirement it was supposed to satisfy.
The fix is not more documentation. It is a small, enforceable link between four things that already exist in most repositories: the requirement, the design decision behind it, the tests that prove it, and the commits or pull requests that changed it.
Once that link exists as data rather than as a shared understanding, you can query it. You can ask which requirements have no test coverage, which tests no longer map to any requirement, and which files changed in a pull request without a matching requirement ID. That query is the actual deliverable of this article, and the rest of the post walks through how to build it with tools you likely already run.
