Are you spending hours crafting the perfect prompts for AI coding assistants? Here are 5 battle-tested prompt patterns that will instantly improve your AI pair programming sessions.
1. The Bug Detective Pattern
I have a bug in my [language] code. Here's what happens:
- Expected: [expected behavior]
- Actual: [actual behavior]
- Error: [error message]
Code:
[paste code]
Walk me through debugging this step by step. Check for:
1. Logic errors
2. Off-by-one errors
3. Null/undefined cases
4. Type mismatches
This pattern works because it gives the AI structured context instead of just "fix my code."
2. The Architecture Review Pattern
Review this architecture decision:
- Current: [what we have]
- Proposed: [what we want to change]
- Constraints: [time, budget, team size]
- Scale: [expected users/requests]
Evaluate trade-offs and suggest the best approach.
3. The Test Generator Pattern
Generate comprehensive tests for this function:
[paste function]
Include:
- Happy path tests
- Edge cases (empty input, null, max values)
- Error cases
- Performance considerations
Use [testing framework] syntax.
4. The Code Review Checklist
Review this PR/code change as a senior developer:
[paste code]
Check for:
- Security vulnerabilities
- Performance issues
- Error handling gaps
- Code style consistency
- Missing edge cases
Format: list each issue with severity (critical/warning/info).
5. The Refactor Guide
Refactor this code for better [readability/performance/maintainability]:
[paste code]
Requirements:
- Keep the same external API/interface
- Add types/annotations
- Extract reusable functions
- Improve naming
Show before/after with explanations.
Why These Work
Each pattern follows three principles:
- Structured input — AI performs better with organized information
- Explicit expectations — Tell the AI exactly what format you want
- Constraint boundaries — Limit scope to get focused answers
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What prompt patterns work best for you? Drop a comment below!
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