Skip to main contentQuick Overview
- 👍 Thumbs up: Kody learns what your team likes
- 👎 Thumbs down: Kody learns what to avoid
- ✨ Auto-learning: Kody tracks which suggestions get implemented
How the Learning Works
1. Collecting Feedback
Kody learns from three main sources:
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Direct Reactions: Team members can react to Kody’s suggestions on any code management tool:
- 👍 = “This is what we want”
- 👎 = “This doesn’t match our style”
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Implementation Tracking: When your team implements Kody’s suggestions, she marks it as positive feedback
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Pattern Recognition: Kody builds knowledge clusters based on your team’s preferences
2. Smart Filtering
Once Kody has enough data, she:
- Analyzes new code suggestions
- Compares them against your team’s preference clusters
- Only shows suggestions that match your team’s style
- Filters out suggestions similar to previously rejected ones
Why Your Feedback Matters
The more feedback you provide, the better Kody becomes at:
- ✅ Matching your coding style
- 🎯 Making relevant suggestions
- 🚫 Avoiding unwanted patterns
- 💡 Understanding team preferences
Best Practices
- Be Consistent: Encourage the team to provide feedback regularly
- React Promptly: Give feedback while the context is fresh
- Team Alignment: Ensure the team agrees on what makes a good suggestion
