How do you decide when an AI-generated code change is safe to merge?

[MrOptor]

Discussion Type

Question

Discussion Content

I've started using AI tools more regularly during development, and one thing I'm still figuring out is how much review is enough before accepting an AI-generated change.

For small changes, reviewing the diff and running the existing tests seems straightforward. But for larger changes, an AI-generated solution can look reasonable while still making assumptions about the project's architecture or introducing edge cases.

How do you personally review AI-generated code before merging it?

Do you rely mainly on tests and code review, or do you have a particular workflow for checking things like hidden edge cases, dependencies, security issues, and consistency with the existing codebase?

I'd be interested in hearing how other developers approach this, especially for larger changes.

[gnallamoth]

For larger changes, I review the diff and check the architecture, dependencies, error handling, security, and edge cases. I also use coding-agent skills/rules for a second pass—for example, a security review skill, test-coverage check, dependency check, or a rule to verify that new code follows existing project patterns.

I still manually review the critical parts and run the tests rather than relying only on the agent.

[tushar240907]

For larger changes, I review the diff and check the architecture, dependencies, error handling, security, and edge cases. I also use coding-agent skills/rules for a second pass—for example, a security review skill, test-coverage check, dependency check, or a rule to verify that new code follows existing project patterns.

I still manually review the critical parts and run the tests rather than relying only on the agent.