Add Compound Engineering job to library

[nhorton]

Summary

Adds a complete DeepWork implementation of the Compound Engineering methodology, inspired by Every Inc's Compound Engineering Plugin. This job provides a structured workflow for high-quality engineering work that compounds knowledge over time rather than accumulating technical debt.

Key Changes

• New job: library/jobs/compound_engineering/ with complete implementation
  • job.yml: Job definition with 4 steps (plan, work, review, compound) and 3 workflow combinations
  • readme.md: Comprehensive documentation including:
    • Overview of the Compound Engineering philosophy
    • Installation and usage instructions
    • Detailed analysis of what DeepWork provides automatically vs. what the original plugin had
    • 10 feature gaps and 10 suggestions for improving DeepWork based on this implementation
    • Philosophy and credits
  • steps/plan.md: Create detailed implementation plans through idea refinement, codebase research, and prior learning checks
  • steps/work.md: Execute plans systematically with task tracking and incremental commits
  • steps/review.md: Multi-perspective code review with 8 specialized review angles
  • steps/compound.md: Document solutions and learnings for future reuse

Implementation Details

The Four-Step Workflow

1. Plan (40%): Transform feature ideas into detailed implementation plans with codebase research
2. Work (20%): Execute plans with task tracking and continuous testing
3. Review (30%): Multi-perspective code review before merging
4. Compound (10%): Document solutions and learnings for institutional knowledge

Core Philosophy

• 80/20 split: 80% planning and review, 20% execution
• Knowledge compounds: Each solved problem becomes searchable documentation for future work
• Multiple perspectives: Reviews use 8 different specialized angles (security, performance, patterns, etc.)
• Incremental execution: Small commits with continuous testing maintain quality

Notable Features

• Interactive planning with codebase research using sub-agents
• Multi-perspective code review with severity categorization (P1/P2/P3)
• Structured solution documentation in docs/solutions/ with categories
• Quality criteria for each step to ensure consistency
• Comprehensive readme analyzing gaps and suggesting DeepWork improvements

Why This Matters

This job demonstrates how DeepWork can replicate sophisticated AI engineering workflows while being simpler and more portable than the original plugin. The readme's analysis of gaps and suggestions provides valuable feedback for improving the DeepWork platform itself.

The Compound Engineering methodology is particularly valuable for teams wanting to reduce technical debt over time through systematic quality practices and knowledge capture.

https://claude.ai/code/session_01EKw7Tc1vwYAH96kaDfq8xY