"Code complete" and "ready to ship" are different states. Before I call a project finished, I want a review strategy that asks more than one question: does the code work, is it secure enough for its purpose, is the design understandable, do the tests support the claims, and can another person maintain it?
AI helps me plan those reviews before it helps execute them. I can define the review lenses, create focused prompts, and then ask a tool to inspect the work from each angle. That is more useful than the vague instruction to "do a code review," because it makes the expected evidence explicit.
This approach also makes short development cycles more useful. A small, testable slice gives me something concrete to review before the next slice adds more complexity. It is not bureaucracy for its own sake; it is a way to keep the work inspectable while moving quickly.
AI can generate tests and review findings early, but it does not eliminate the need for user acceptance testing or a final human decision. The win is that I spend my attention on the questions that require judgment instead of discovering the obvious issues late in the process.