Debugging AI-Generated Code

Everything breaks. The difference between a builder who ships and one who gives up is not talent, it is a method for what to do when something goes wrong. Debugging AI-generated code has its own particular challenges: you did not write it, you may not fully understand it, and the AI that broke it will confidently offer to fix it, sometimes making things worse.

Debugging AI-Generated Code gives you that method. You will learn to read error messages as clues rather than scoldings, isolate a bug by narrowing rather than guessing, hand the AI exactly what it needs to produce a repair that actually lands, and recognise the death spiral where every fix breaks something new. Most importantly, you will learn when to stop trusting the AI, revert to your last working state, and try a different way. You finish with a systematic method for rescuing any broken project.

This is a practical, calming course, taught in plain language with clear diagrams and small examples, and it is tool-agnostic. It suits anyone who builds with AI. Each module blends a short video overview, illustrated lessons, a knowledge-check quiz, and a hands-on interactive activity, including a bug-hunt that teaches you to find a fault by halving.

What you will be able to do:

• Read an error message and know exactly what it is telling you.
• Tell apart the kinds of wrong: crashes, silent wrong answers, hangs, and works-for-me.
• Reproduce a bug reliably and isolate it by narrowing, not guessing.
• Give an AI a bug report that produces a repair that actually works.
• Spot the death spiral, revert to a working state, and change approach.
• Rescue a broken project with a calm, repeatable method.

Who it is for: Anyone who builds with AI and has watched a working project stop working. No deep coding background required.

Course outline: Orientation · Reading Errors · Isolating the Bug · Directing AI Repairs · When to Stop Trusting the AI · Capstone: Rescue a Broken Project.