Overview
Goal: Ensure AI code assistants generate correct, readable, maintainable code. Time Investment: 30 minutes to first insightsThe Challenge
You’re building a code assistant for your developers. Questions:- How correct should generated code be?
- What code style matters?
- How should explanations be written?
- When should the AI say “I don’t know”?
Quick Example: Python Code Assistant
Step 1: Create Project
System Prompt:Step 2: Add Scenarios
Step 3: Generate, Rate, Extract
Rate based on:- Correctness: Does code work?
- Style: Follows PEP 8?
- Clarity: Easy to understand?
- Comments: Well-explained?
Step 4: Get Insights
Patterns reveal:- All 5-star: Code has clear variable names
- All 5-star: Includes example usage
- Low-star: Missing error handling
- Low-star: Overly complex when simpler solution exists
Scenarios by Language
Python
JavaScript
Go/Rust/etc.
Similar patterns for other languages.Key Metrics for Code Quality
What Makes Code “5-Star”?
- Correctness: Works as expected
- Readability: Clear variable names, good structure
- Efficiency: No unnecessary complexity
- Safety: Handles edge cases and errors
- Best Practices: Follows language conventions
Common Failure Patterns
Pattern 1: Incorrect Implementation- 5-star: Correct algorithm
- 1-star: Off-by-one errors, wrong logic
- 5-star:
count_active_users() - 1-star:
x = 5
- 5-star: Handles edge cases, throws meaningful errors
- 1-star: Assumes happy path, crashes on edge cases
- 5-star: Clear step-by-step explanation
- 1-star: Assumes reader knows everything
Evaluation Tips
For Generated Code:- Test it (does it compile/run?)
- Check correctness (does it solve the problem?)
- Review readability (would you merge this?)
- Consider efficiency (any obvious optimizations?)
- Is it accurate?
- Is it at the right level of detail?
- Would a junior dev understand it?
- Does it include examples?
Iteration Example
Iteration 1 (60% success):- Issue: Code is correct but missing comments
- Fix: Add “Include clear comments for complex logic”
- Issue: Doesn’t handle edge cases
- Fix: Add “Include error handling and edge case checks”
- Issue: Explanations assume too much knowledge
- Fix: Add “Explain assumptions and provide beginner-friendly context”
Export for Engineering
- Export golden examples (5-star code snippets)
- Extract patterns (best practices discovered)
- Use in:
- Code review guidelines
- Junior dev training
- CI/CD integration (syntax checking)
- Documentation of expected behavior