Stop spending hours hunting for bugs. These AI debugging prompts help you systematically identify, analyze, and fix issues in your code—from cryptic error messages to complex logic bugs.
In short: The best debugging prompts include your specific context, define the expected output format, and mention the tools or frameworks involved. Browse the curated collection below and customize any prompt to your workflow.
Quickly interpret cryptic error messages and stack traces
Systematic root cause analysis approach
Get multiple solution options ranked by likelihood
Learn debugging techniques as you solve problems
Always include the full error message and stack trace
Describe what you expected vs what happened
Include relevant code snippets with context
Mention your environment (OS, versions, dependencies)
Share enough context for AI to understand the problem—usually the function with the bug, related functions it calls, and any relevant type definitions. Avoid sharing your entire codebase; focus on the relevant portions.
Never. Always understand the suggested fix before applying it. AI can sometimes suggest fixes that work for the immediate symptom but introduce new issues. Test thoroughly after any AI-suggested change.
Yes, but be careful with sensitive data. Remove or anonymize any PII, credentials, or proprietary information before sharing logs or error details. Focus on the error patterns rather than actual data.
Browse our complete prompt library or contribute your own.