Using AI to Check Your Logic
You've written your loops and conditions, and they seem to work. But do they handle every situation? AI coding agents can act as a second pair of eyes, spotting logical gaps and edge cases you might overlook.
Asking AI to Review Logic
When you want AI to check your control flow, be specific about what you're trying to accomplish. Don't just paste code — explain your intent.
Good prompt:
"This function should return True if a user is eligible for a discount (age over 65 OR a premium member). Does my logic handle all cases correctly?"
Then show your code:
def is_eligible(age, is_premium):
if age > 65:
return True
elif is_premium:
return True
return False
AI might point out that your logic is correct but could be simplified to return age > 65 or is_premium.
Finding Edge Cases
Edge cases are unusual inputs that might break your logic. AI is particularly good at thinking of these:
- "What happens if the list is empty?"
- "What if the user enters a negative number?"
- "What if someone passes
Noneinstead of a string?"
Example prompt:
"What edge cases should I handle for this input validation that checks if a username is valid (3-20 characters, letters and numbers only)?"
AI might suggest testing: empty strings, strings with spaces, strings with special characters, strings that are exactly 3 or 20 characters, and None values.
Verifying Loop Behavior
Loops are easy to get subtly wrong. Ask AI to trace through your logic:
- "Will this loop ever be infinite?"
- "Does this loop process the last item correctly?"
- "Review this if/elif/else chain for gaps."
Trust but Verify
AI suggestions are helpful, but they're not infallible. When AI points out a potential issue:
- Understand the concern — don't just blindly change code
- Test the scenario — actually run the edge case
- Decide if it matters — some edge cases are theoretical and won't occur in your use case
AI is a thinking partner, not an oracle. Use it to expand your thinking, then apply your own judgment.