This guide is written for developers who want a practical answer, not a giant theory dump. The goal is to help you understand the decision, use the idea in a real project, and explain it clearly in an interview or code review.

Quick answer

Review AI-generated code like code from a fast junior developer: useful, but not automatically correct.

Why developers search this

AI coding usage is high, but trust is lower; review checklists match real developer anxiety.

It is a good SEO topic because the search usually happens near a real task: fixing a broken build, choosing an architecture pattern, deploying an app, reviewing AI-generated code, or preparing portfolio proof. Those searches are more valuable than broad “what is programming?” traffic because the reader needs an answer they can use today.

Mental model

The risk is not that AI writes bad code every time. The risk is that it writes plausible code you stop questioning.

Check Question
Correctness Does it solve the actual requirement?
Security Did it introduce unsafe input, secrets, or auth gaps?
Maintainability Can the team understand it later?
Tests Does failure behavior have coverage?

Practical example

Before merge:
1. Explain the code in your own words
2. Run tests and type checks
3. Check edge cases
4. Check security-sensitive paths
5. Remove fake abstractions

This example is intentionally small. In a real codebase, the surrounding details matter: naming, error handling, tests, runtime config, permissions, and how easy the next developer can understand the change.

Implementation checklist

  • Ask the tool for assumptions it made.
  • Read every changed line.
  • Run tests locally.
  • Add tests for edge cases.
  • Delete code you cannot explain.

Common mistakes

  • Merging because the code compiles.
  • Trusting invented APIs.
  • Skipping security review.
  • Leaving verbose generic abstractions.
  • Not checking license or source assumptions for copied snippets.

How to explain this in an interview

Use a concrete sentence:

I used this pattern because [problem]. The main tradeoff was [tradeoff]. I verified it by [test or check].

That structure works because it shows judgment. Anyone can name a tool. Strong developers explain why they chose it, what could go wrong, and how they checked the result.

Sources checked

Final takeaway

Review AI-generated code like code from a fast junior developer: useful, but not automatically correct. Keep the implementation small, verify the edge cases, and write the decision down so the next person can trust it.