AI Code Review: The Hidden Dangers of "Clean" Code

A pull request was approved in under two minutes recently. It involved fourteen files, a retry wrapper, a small refactor, and one new dependency. The code was AI-generated, lightly prompted, and quickly accepted. What's interesting is that the code looked clean and unremarkable. Reviewers had no reason to question why specific choices were made, like the backoff strategy or a particular dependency. The code appeared to be a textbook implementation of a known pattern. However, the diff didn't explain critical details, such as why there were three attempts instead of five, or why a five-second timeout was chosen. These details were unknown to both the reviewer and often the developer. This gap between correct code and understood code can lead to problems later on. The bottom line is that reasonable-looking AI-generated code can hide a lack of underlying reasoning, which code review isn't designed to catch.