Reviewing AI-Generated Code
AI can generate impressive code quickly, but it also makes confident mistakes. The code might look correct, run without errors, and still be subtly wrong. Your job is to review AI output critically before using it.
Read and Understand First
Before copying any AI-generated code, read through it line by line. Ask yourself: do I understand what this code does? If you can't explain it, you shouldn't use it.
This isn't just about catching bugs — it's about learning. When you understand the code, you can modify it, debug it, and build on it later.
Test With Various Inputs
AI often generates code that works for the example you provided but fails on edge cases. Test thoroughly:
- Normal inputs: Does it work for typical cases?
- Empty inputs: What happens with an empty list or string?
- Boundary values: Zero, negative numbers, very large values
- Invalid inputs: What if someone passes the wrong type?
Run the code yourself. Don't assume it works because the AI said it does.
Watch for Common AI Mistakes
AI tends to make certain types of errors:
- Hardcoded values that should be parameters
- Missing error handling for edge cases
- Outdated syntax from older language versions
- Security issues like unsanitized user input
- Inefficient approaches that work but perform poorly
Use a Review Checklist
Before accepting AI code, run through these questions:
- Do I understand what every line does?
- Does it handle the inputs I described?
- What happens with edge cases?
- Are there any security concerns?
- Does it follow good coding practices?
- Is there unnecessary complexity?
Trust but Verify
AI is a powerful assistant, but you're the developer responsible for the code. Think of AI suggestions like advice from a colleague — valuable input that you evaluate and decide whether to use.
The goal isn't to catch every AI mistake immediately. It's to develop the habit of critical evaluation that will serve you throughout your career.