When I've worked with systems that had these kinds of characteristics, we had checklists. A long list of "have you thought of X". You can't rely on someone writing a design to think of these things either! You need to have a process, and the process applies whether you dive into the code, dive into the spec, or have an AI dive into either.

It's orthogonal.

To be clear, I'm not suggesting blindly deploying an AI-written spike implementation to production, but rather using it to elicit information for better designs.

The fact that a probe that goes off and modifies tables X, Y and Z to achieve the feature gives information for an AI auditor to look for other uses of X, Y and Z, and discover things humans may miss, because with good guidance and a proper harness, AI is usually more persistent and thorough than people. It can turn search results into a checklist and the harness can track completion, and so on. I am far from convinced that your example would not be found via this route.