continual-learning

# Continual Learning for AI Coding Agents Your agent forgets everything between sessions. Continual learning fixes that. ## The Loop ``` Experience → Capture → Reflect → Persist → Apply ↑ │ └───────────────────────────────────────┘ ``` ## Quick Start Install the hook (one step): ```bash cp -r hooks/continual-learning .github/hooks/ ``` Auto-initializes on first session. No config needed. ## Two-Tier Memory **Global** (`~/.copilot/learnings.db`) — follows you across all projects: - Tool patterns (which tools fail, which work) - Cross-project conventions - General coding preferences **Local** (`.copilot-memory/learnings.db`) — stays with this repo: - Project-specific conventions - Common mistakes for this codebase - Team preferences ## How Learnings Get Stored ### Automatic (via hooks) The hook observes tool outcomes and detects failure patterns: ``` Session 1: bash tool fails 4 times → learning stored: "bash frequently fails" Session 2: hook surfaces that learning at start → agent adjusts approach ``` ### Agent-native (via store_memory / SQL) The agent can write learnings directly: ```sql INSERT INTO learnings (scope, category, content, source) VALUES ('local', 'convention', 'This project uses Result<T> not exceptions', 'user_correction'); ``` Categories: `pattern`, `mistake`, `preference`, `tool_insight` ### Manual (memory files) For human-readable, version-controlled knowledge: ```markdown # .copilot-memory/conven...