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Quick Overview

  • 👍 Thumbs up: Kody learns what your team likes
  • 👎 Thumbs down: Kody learns what to avoid
  • ✨ Auto-learning: Kody tracks which suggestions get implemented

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How the Learning Works

Kody Learnings

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1. Collecting Feedback

Kody learns from three main sources:
  • 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”
  • Implementation Tracking: When your team implements Kody’s suggestions, she marks it as positive feedback
  • Pattern Recognition: Kody builds knowledge clusters based on your team’s preferences

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2. Smart Filtering

Once Kody has enough data, she:
  1. Analyzes new code suggestions
  2. Compares them against your team’s preference clusters
  3. Only shows suggestions that match your team’s style
  4. Filters out suggestions similar to previously rejected ones

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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

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Best Practices

  1. Be Consistent: Encourage the team to provide feedback regularly
  2. React Promptly: Give feedback while the context is fresh
  3. Team Alignment: Ensure the team agrees on what makes a good suggestion