A quick question: How do you currently review AI-Generated Code Changes?
A discussion on reddit.com highlights the complexities of reviewing AI-generated code. While AI coding agents can produce functional code, the community notes that "the code works" does not equate to "this is the right change." AI-generated changes might pass tests but still introduce architectural violations, technical debt, or address symptoms rather than root causes, often modifying files outside the intended scope. The conversation seeks methods for effectively reviewing these AI-generated code changes.
- Published
- Sep 7, 2026, 05:46
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- Dev community
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- Community
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'Cause One thing AI coding agents have made very obvious to me: "the code works" and "this is the right change" are not the same thing.
A change can pass tests and still violate the repo architecture, cross a boundary it should not touch, introduce a shortcut that becomes technical debt, solve the symptom instead of the real failure and change files that were outside the plan.
So let me know how you do it...