convergence-compound

To document learnings after fixing a bug, draft a structured learning artifact with YAML frontmatter fields like problem_type, module, severity, and tags, alongside a generalizable Rule for future reuse. This ensures post-work knowledge compounds over time.

Post-work learning documentation should include a structured body covering What Happened, Root Cause, Fix, and a generalizable Rule, plus YAML frontmatter with problem_type, module, severity, and tags to ensure the knowledge is reusable.

You need to capture a reusable learning artifact after completing non-trivial tasks such as debugging, code review, or feature delivery. Applying this process ensures that solved problems are codified and available for future reference.

To prevent duplicate knowledge management entries, the learning capture workflow checks for overlap with existing learnings and presents drafts for human correction before saving. This ensures your knowledge base remains clean and non-redundant.

Yes, the learning artifact workflow requires manual review; it generates a draft from your activity and explicitly presents it for human correction before saving to ensure accuracy and generalizability of the captured knowledge.