compound-learnings

# Compound Learnings Transform ephemeral session learnings into permanent, compounding capabilities. ## When to Use - "What should I learn from recent sessions?" - "Improve my setup based on recent work" - "Turn learnings into skills/rules" - "What patterns should become permanent?" - "Compound my learnings" ## Process ### Step 1: Gather Learnings ```bash # List learnings (most recent first) ls -t $CLAUDE_PROJECT_DIR/.claude/cache/learnings/*.md | head -20 # Count total ls $CLAUDE_PROJECT_DIR/.claude/cache/learnings/*.md | wc -l ``` Read the most recent 5-10 files (or specify a date range). ### Step 2: Extract Patterns (Structured) For each learnings file, extract entries from these specific sections: | Section Header | What to Extract | |----------------|-----------------| | `## Patterns` or `Reusable techniques` | Direct candidates for rules | | `**Takeaway:**` or `**Actionable takeaway:**` | Decision heuristics | | `## What Worked` | Success patterns | | `## What Failed` | Anti-patterns (invert to rules) | | `## Key Decisions` | Design principles | Build a frequency table as you go: ```markdown | Pattern | Sessions | Category | |---------|----------|----------| | "Check artifacts before editing" | abc, def, ghi | debugging | | "Pass IDs explicitly" | abc, def, ghi, jkl | reliability | ``` ### Step 2b: Consolidate Similar Patterns Before counting, merge patterns that express the same principle: **Example consolidation:** - "Artifact-first debugging" - "Verif...