AI Code Review
AI can produce code quickly. That does not mean it is safe to trust.
Redfield reviews AI-assisted code for bugs, unsafe assumptions, false confidence, maintainability problems and places where the output does not match the intended behaviour.
Check the code before you build on it.
ChatGPT, Copilot, Cursor and similar tools can create convincing code that hides fragile logic, security mistakes, dependency confusion, missing edge cases or a total misunderstanding of the real requirement.
An AI code review is not a full audit. It is a focused technical review to help you understand whether the code is a usable prototype, too risky to extend, or ready for a targeted repair.
When this helps
- You generated a prototype and need to know what it really is.
- The code runs locally but feels fragile.
- You need a developer-readable risk note.
- You want to learn what the AI output is doing.
- You need to decide whether to repair or restart.
Review focus
Behaviour
Does the code appear to do what it was meant to do?
Risk
Where are the obvious bugs, unsafe assumptions or weak dependencies?
Next step
Should you repair it, rebuild it, reduce scope or stop relying on it?
Have AI-generated code you do not trust?
Describe the goal, the generated code, and what you need to decide next.