Conclusion

You have now run two structured AI review prompts against the same app, compared both outputs against your own manual findings, and made deliberate accept, reject, and investigate-further decisions on every finding.

Key Takeaways

• AI is most useful as a second reviewer, not the primary one. Forming your own judgment first makes the comparison meaningful.
• An open prompt goes deep on what it happens to notice. A checklist-guided prompt goes wide across every category. Use both when coverage matters.
• The checklist changes not just what gets found, but how findings get classified. The same issue can appear under different categories depending on whether you asked for structure or not.
• Accepting, rejecting, and investigating further are all valid responses to an AI finding. The goal is your judgment, not AI’s.
• Asking AI to classify each finding as a real bug or a style preference before acting on anything keeps the list manageable and prevents style preferences from getting treated with the same urgency as crash risks.
• A review that tries to fix everything at once fixes nothing well. Scope is a human decision.

In the next lesson, you’ll make these standards permanent. So the next time AI writes code for this project, it already knows what you care about.