aif-verify

To verify AI implementation against a project plan, run a post-implementation review that checks task completion, ensures code compiles, tests pass, and documentation is updated according to the original requirements.

A post-implementation code review for AI-generated work covers validating task completion, checking that code builds, confirming tests pass, verifying documentation updates, and ensuring dependencies align with the planned governance gates.

You can check if AI code generation missed tasks by validating the completed work against the original plan and task status, which produces a structured verification report with specific remediation guidance for any gaps.

Yes, verification checks if dependencies align with the project plan by validating task completion against the planned requirements, ensuring governance gates are respected, and confirming that all documentation is accurately updated.

You should run an implementation verification check during post-implementation reviews, specifically after completing implementation or fix requests, or when you need to confirm whether any planned tasks or quality standards were missed.