Artificial intelligence (AI)-generated code has become increasingly integrated into the development workflows of many teams. This generated code may appear clean and perfect, but it can fail in unexpected ways.

From my background in software testing, I’ve seen how even minor oversights can cause significant problems once real users are involved.

We’ll walk through beginner-friendly examples of AI mistakes (missing edge cases, hidden bugs, overcomplicated solutions) and share practical steps anyone can use to test and validate AI-assisted code before shipping it.

You’ll leave with practical habits for coding safely with AI.