continuous-learning

Automate pattern extraction by running a Stop hook at session end to observe ProductionOS analytics, identify recurring session patterns, and generate structured instincts automatically.

Continuous learning instincts are atomic, reusable patterns extracted from session observations. They use confidence scoring to determine when a pattern is reliable enough to be promoted globally across projects.

High-confidence patterns are promoted globally through an auto-promotion mechanism that evaluates confidence scores from extracted session data, enabling scalable cross-project reuse of validated instincts.

Yes, a Stop hook is required to generate session instincts. It triggers at session end to update the instincts directory and process ProductionOS analytics data for pattern extraction.

Build a reusable library by integrating a Stop hook, configuring an instincts directory, and applying confidence scoring to automatically extract and promote high-value session patterns across all projects.

Continuous learning requires a confidence scoring mechanism to ensure only high-confidence, validated patterns are promoted globally, preventing low-quality session observations from polluting the reusable instincts library.