Most code review processes produce one artifact: a merged PR. Someone approved it. The review presumably happened. But if an auditor asks you to prove that the AI-generated function in your auth service passed your risk policy — that the model was on your allowlist, that the risk score was below threshold, that a human actually approved it — what do you hand them?
A closed PR is not evidence of the above. It is evidence that someone clicked "Approve." The model identity, the risk state at merge time, whether the reviewer read the AI context or just the diff — none of that is in the PR.
This is the gap that machine-verifiable AI code certificates close.
The Problem Is Structural
When you merge AI-generated code today, you lose the generation context permanently. The commit records the diff. Git blame records the author. Nothing records which model generated it, what the prompt was, what the risk score was at insertion, or whether the human reviewer actually engaged with the full AI context.
