continuous-learning-v2

Automate AI learning from Copilot CLI session analysis by enabling observation hooks that capture user interactions, detect patterns via background agents, and generate confidence-scored instincts for skill evolution.

An instinct-based learning system observes your Copilot CLI sessions to create atomic, confidence-scored instincts from repeated workflows or error resolutions, which then evolve into reusable skills, commands, or agents.

Evolve repeated CLI error resolutions into reusable commands by enabling session observation hooks; the system detects recurring correction patterns, creates instincts with confidence scoring, and clusters them into new commands or agents.

Session observation requires no external dependencies to start learning; it operates entirely locally by utilizing Copilot CLI hooks and background agents to store observations and generate instincts within your environment.

The best way to detect repeated workflow patterns in Copilot CLI is using background agents that observe sessions via hooks, identify recurring user corrections, and generate atomic instincts with confidence scoring for evolution.