continuous-learning-v2

To automate learning from AI development sessions, you enable observation hooks that monitor interactions and identify recurring workflows. The system generates atomic instincts with confidence scores, evolving them into reusable skills, commands, or agents over time.

Instinct-based pattern recognition observes AI sessions to create small, atomic instincts with confidence scores. It uses pattern detection and clustering to evolve these instincts into complex skills, commands, and agents for workflow optimization.

To set up session observation hooks for Claude Code, add the provided JSON configuration to your `~/.claude/settings.json` file. This enables the system to monitor sessions and store observations locally for pattern extraction.

The learning system stores all observations locally and does not require external cloud storage. It operates in the background using a Haiku model for analysis, processing session data to detect patterns and generate instincts.

Use automated skill creation when you notice recurring workflows, frequent user corrections, or repeated error resolutions in your AI sessions. For highly variable or one-off tasks, manual configuration may be more efficient than waiting for pattern clustering.