AI Code Review: Beyond Syntax

Code that compiles is not necessarily code that is safe, correct or maintainable. A review of AI-generated changes should start with the intended behavior: does the implementation solve the requirement, including less obvious states and invalid input?

Follow data from the user interface to storage and external services. Check authorization at the point where protected data is used, how failures are handled, and whether secrets or personal information can be exposed in logs or responses.

Look at the change in the context of the application. Does it follow existing conventions? Are dependencies appropriate? Could the implementation introduce unnecessary queries, slow paths or duplicated logic? A technically valid snippet may still be a poor fit for the system.

Finally, run focused tests and inspect the actual diff. AI tools can help explain code or identify questions, but accountable review requires understanding the product, its threat model and its operating environment.

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