continuous-learning-v2

You can capture tool sessions by enabling observation hooks, which identify patterns and convert them into atomic instincts with confidence scores that evolve into reusable skills.

An instinct-based learning system captures tool use patterns from sessions, creates atomic confidence-weighted instincts, and clusters them through an evolution pipeline into deployable commands or agents.

You turn recurring patterns into commands by using the evolution pipeline to cluster captured instincts, gradually evolving them into structured modules like commands, skills, or agents across projects.

Yes, the learning system ensures safety and privacy by keeping session data entirely local, exporting only summarized instincts to share patterns without exposing raw workspace information.

The best way to start evolving instincts is to enable observation hooks, initialize the directory structure, and let the Haiku-based observer capture feedback loops to build confidence scores.

Yes, you can use hook-based observation with high determinism to automatically track tool use patterns and feedback loops, creating atomic instincts that grow into functional modules.