Just like AI can give wrong answers, AI can write buggy code. Here is what to watch for.
5 min · Reviewed 2026
The big idea
AI is great at writing code that LOOKS right. But sometimes the code does not actually work. Or it works but does the wrong thing. You have to test the code to be sure.
Some examples
AI might use a function that does not exist (made-up).
AI might write code that runs but gives the wrong answer.
AI might forget to handle a special case (like what if there are zero items in a list).
AI might use an old way of writing code that does not work anymore.
Try it!
Next time you (or a grown-up) tries AI-coded help, give it a hard test on purpose. Try giving it nothing, or a huge number, or a weird input. See what breaks.
End-of-lesson check
8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-explorers-ai-coding-AI-is-not-perfect-coder
What is the main idea of "AI Coders Make Mistakes Too: How to Spot Them"?
Just like AI can give wrong answers, AI can write buggy code. Here is what to watch for.
Use AI as the final authority for the whole decision
Avoid checking the answer once it sounds polished
Focus only on speed instead of judgment
Which concept is most central to "AI Coders Make Mistakes Too: How to Spot Them"?
AI mistakes
bugs
code review
testing
Which use of AI fits this topic best?
Let the AI decide what matters without your review
Use the answer before checking whether it fits the situation
AI might use a function that does not exist (made-up).
Trust the first answer because it sounds confident
What should a careful learner remember about "The rule"?
Always test code AI writes. Run it. Try weird inputs. If something does not look right, ask AI to fix it OR ask a grown-up.
Skip the context so the tool can guess faster
Treat the output as private even after sharing it online
Use the answer without checking the source
You want to use AI after this lesson. What is the safest next step?
Act immediately because the AI answer is written clearly
Use short, concrete wording and ask a trusted adult when the stakes matter.
Hide uncertainty so the final answer looks cleaner
Use private or sensitive details before checking permission
How should AI output about bugs be treated?
As proof that no other source is needed
As a replacement for context, consent, or expert review
As a draft or helper output that still needs human judgment and verification
As something that becomes correct when it sounds confident
Name one way to verify an AI answer about bugs.
Which action would help you apply "AI Coders Make Mistakes Too: How to Spot Them" responsibly?
Use the tool to avoid thinking through the tradeoff
Keep going even if the output conflicts with a trusted source
Trust the first answer because it sounds confident
AI might write code that runs but gives the wrong answer.
