retro

Automating lessons learned capture from completed stories involves collecting insights from git logs and Linear issue comments, appending them to a documentation ledger, and proposing rule changes for team improvement. The process triggers when a story is marked Done.

Story retrospective automation for team improvement is the process of distilling insights from completed work items to update documentation and propose role-specific rule changes. It ensures valuable lessons are systematically captured and applied to future work.

To run a retrospective using git logs and Linear issue comments, you invoke the automation tool with a specific story identifier. The system extracts historical data from these sources to analyze completed work and draft lessons.

Yes, you need access to specific files to update rules during a story retrospective. The automation requires permissions to read git logs and Linear comments, and write access to rule files to propose role-specific improvements.

You should run an automated story retrospective for lessons capture immediately after a story is marked as Done. This timing ensures that historical context is fresh and valuable lessons are accurately documented for future team improvement.

The best way to capture lessons learned from completed Linear issues is automating the extraction of issue comments and git logs. This approach appends insights directly to a ledger and proposes rule updates without manual documentation overhead.