What code review process do you use for AI-generated code?

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— Originally published at dev.to

I have been thinking about this a lot lately.

As AI tools become part of daily development, generating code is getting easier. But reviewing that code properly is still very important.

I want to learn how other developers handle this.

When AI generates code for you, what review process do you follow before you keep it?

I am interested in questions like:

  • Do you review everything line by line?
  • Do you trust AI for boilerplate only, or also for business logic?
  • What do you check first: correctness, security, performance, readability, or architecture?
  • Do you use a checklist?
  • How do you catch subtle bugs or bad assumptions?

My rough thinking is something like this:

  • understand the code fully before keeping it
  • verify logic against requirements
  • test happy path and edge cases
  • check security and performance concerns
  • refactor to match project standards
  • never merge code only because “it works”

I would really like to hear practical workflows from real developers and teams.

What is your process for reviewing AI-generated code?

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Surat, Gujarat, Indiamanthanbhatt.dev
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I am a passionate and results-driven Software Engineer with a strong foundation in developing robust and scalable applications. My expertise encompasses a wide range of programming... Show more
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