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Reaction-based fine-tuning is not currently active. 👍/👎 reactions and suggestion implementation status can be recorded, but they do not train a model, build preference clusters, or filter the next review.
A thumbs-up or thumbs-down alone does not explain why a suggestion was rejected. Richer negative-feedback context is needed before this learning loop can be reintroduced. You can still leave reactions as optional product feedback. Do not expect reacting to a suggestion to automatically suppress similar suggestions in later reviews.

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What affects future reviews

  • Memories: Persist explicit team conventions through @kody remember and conversations.
  • Kody Rules: Define standards that are applied during code review.
  • Automatic Rules Generation: Generate rules from review history (active by default, or held in Pending review for approval when Kody knowledge approval is on). This is separate from reaction-based fine-tuning and remains an active feature.