ChatGPT Prompts for Debugging: Find and Fix Bugs Faster
ChatGPT prompts for debugging code across any language. Systematic bug diagnosis, stack trace analysis, and rubber duck debugging frameworks.
The Prompt
Act as a senior debugging expert who has helped teams eliminate production incidents at scale.
Help me debug the following issue:
Code: [PASTE RELEVANT CODE]
Error message / stack trace: [PASTE EXACT ERROR]
Expected behavior: {what should happen}
Actual behavior: {what is actually happening}
Language/framework: {language, framework, version}
Environment: {dev / staging / production — and any relevant OS, Node version, etc.}
What I've already tried: {steps already taken}
Debug output structure:
1. Root cause hypothesis (ranked by likelihood — most likely first):
- Hypothesis A: [cause] — [why this is likely] — [how to confirm]
- Hypothesis B: [cause] — [why this is likely] — [how to confirm]
2. Step-by-step diagnosis plan (ordered — do these in sequence to isolate the root cause)
3. Fix for most likely cause (include the corrected code, not just a description)
4. How to verify the fix works (specific test or check)
5. Prevention: how to prevent this class of bug from recurring
Constraints:
- Hypotheses must be ranked by likelihood based on the evidence provided
- Confirmation steps must be specific commands or code snippets — not "check your logs"
- Fix must be a complete working code block, not pseudocode
- Prevention must be actionable — a lint rule, a test, or a code pattern change
Variables to fill in
-
{code}The relevant code block — include enough context -
{error message}The exact error text or stack trace -
{expected vs actual}What should happen and what is actually happening -
{what I've tried}Steps already taken — prevents the AI from suggesting things you've ruled out
How to use this prompt
- Always paste the exact error message — paraphrasing it loses critical diagnostic information
- Include 'what I've tried' to skip suggestions you've already ruled out
- Use the diagnosis plan in sequence — don't skip to the fix before confirming the root cause
- Save the prevention step as a comment in your codebase or add it to your lint config
The ‘what I’ve tried’ field is the most valuable input
Telling the AI what you’ve already ruled out is as important as describing the bug. Without it, you’ll get suggestions you’ve already tried — which wastes time and erodes confidence in the output. The ‘what I’ve already tried’ constraint in this prompt converts a generic debugging session into a focused hunt for what you haven’t checked yet.
Stack traces are more informative than error messages
The visible error (‘undefined is not a function’) is often the symptom, not the cause. The stack trace is the diagnostic trail. Paste the complete stack trace — every line of it — into the prompt. The AI can often identify the root cause from the call stack pattern even before looking at the code.
Ranked hypotheses prevent confirmation bias
Debugging in isolation tends toward confirmation bias — you find evidence for the hypothesis you started with and ignore contradicting signals. Asking the AI to generate and rank multiple hypotheses forces you to consider alternatives before committing to an investigation path.
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