AI Can Write Code. But Can You Tell When the Code Is Wrong?

AI Can Write Code. But Can You Tell When the Code Is Wrong? It's easy to be impressed when an AI tool generates a working piece of code in seconds. You describe what you want, it produces the code, and sometimes everything works exactly as expected. But what happens when it doesn't? AI-generated code can contain errors that aren't immediately obvious. A feature might work in one situation and fail in another. A function might return the right result for a simple example but break when given unexpected input. This is why understanding the code still matters, even when AI does most of the writing. Don't just ask AI to fix errors. When something goes wrong, it's tempting to paste the error message into an AI tool and accept whatever solution it suggests. A better approach is to understand three things: - What was the code supposed to do? - What actually happened? - What changed after applying the suggested fix? This helps you avoid fixing one problem while accidentally creating another. Test beyond the happy path. If you've built a form, don't only test it with correct information. Try leaving fields empty, entering unexpected values, and submitting the form more than once. If you've built a calculator, test unusual numbers and edge cases. The point is simple: a feature working once doesn't mean it's reliable. Learn to read what AI produces. You don't need to understand every line of code immediately. But you should gradually learn to recognize what the important parts do, how they connect, and where problems might occur. AI can help you build faster. Understanding what it builds helps you build better. That's the difference between simply generating code and becoming someone who can confidently develop software.