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Every team has unwritten context — technology preferences, naming conventions, architectural decisions, migration details. Instead of documenting them all upfront, you can teach Kody through natural conversation so future reviews are more relevant and repetitive bad suggestions go away.

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How it works

When you talk to Kody in PR comments, it detects when you’re stating codebase context or a team preference and automatically saves it as a Memory. Memories are then applied as high-priority context in all future code reviews and conversations.

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Explicit teaching

Directly tell Kody to remember something:

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Implicit learning

State a preference naturally — Kody picks it up:

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What Kody won’t save

Kody is selective about what becomes a memory:
  • Temporary instructions (“fix this now”, “skip this for today”)
  • Questions (“what’s the deadline?”)
  • Debugging chatter (“I see an error”)
  • Vague statements without actionable information
  • Requests scoped to a single PR or task

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Memory scopes

Each memory applies at a specific level:

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Approval workflow

If you want to review AI-generated memories before they take effect, enable LLM-generated memories approval in settings. Memories will enter a pending state until you approve them.

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Managing memories

Go to Code Review Settings → Kody Rules → Memories tab to view, edit, or delete memories. You can also create memories manually from the UI. For details, see Kody Rules — Memories.