continuous-learning-v2

To capture and reuse AI coding session patterns, background observation hooks automatically extract learned behaviors into atomic instincts. These instincts are managed in project-specific and global knowledge bases, allowing you to retain valuable workflows across sessions.

An atomic instinct is a small, learned behavior captured from your AI interactions with confidence scoring. It represents a discrete piece of reusable knowledge that forms the foundation for automating recurring coding patterns and workflows.

Confidence-weighted pattern detection evaluates the reliability of captured instincts over time. High-confidence instincts are clustered together in an evolution pipeline to automatically generate specialized agents, commands, or skills for your workflow.

Yes, Python 3 is required to run the scripts that power the background observation hooks. This environment is necessary to capture interactions, manage knowledge bases, and automate your coding patterns.

Yes, the system supports project-scoped learning to keep project-specific patterns isolated. Simultaneously, it manages a global knowledge base to share universal best practices across all your different AI sessions.