self-reflect

To document root causes after a stakeholder correction, capture the error details and classify the gap as missing, ambiguous, ignored, or emergent. This structured reflection process records what happened and outlines concrete corrective actions.

Automate reflection documentation by triggering the process immediately after feedback cycles. It automatically writes a structured narrative file with metadata to docs/clasi/reflections/YYYY-MM-DD-slug.md, ensuring learning is codified for future work.

The best way to turn process improvement feedback into a structured reflection is to record the failed decision point, analyze the root cause classification, and propose concrete fixes. Optionally, generate a TODO file to track the implementation of these corrective actions.

Yes, you can automatically generate a TODO file during post-correction reviews. After recording the error details and analyzing the root cause, the process optionally creates a TODO to ensure the proposed corrective actions are implemented.

Use structured reflection in AI-agent workflows immediately after a stakeholder correction or during feedback cycles. It captures what action failed, identifies the root cause, and writes a reflection document to guide future process improvements.