This workflow automates the creation of detailed retrospective reports from Jira issues, specifically when an Epic’s status changes to ‘Done’. It begins by monitoring Jira for issue updates using a Jira trigger. When a relevant issue is marked as ‘Done’, the workflow fetches all issues under the Epic along with their comments. The fetched comments and issue descriptions are then processed and summarized using an OpenAI language model integrated via n8n’s Langchain nodes. The AI generates a comprehensive lessons learned report formatted in Markdown, which is subsequently inserted into a Google Doc, enabling seamless documentation and sharing of retrospective insights.
The key steps include:
– Monitoring Jira for issue status updates.
– Filtering issues to respond only when an Epic is marked as ‘Done’.
– Fetching all relevant issues under the Epic and their comments.
– Using an AI agent to analyze and generate a structured Lessons Learned report.
– Updating a Google Doc with the generated report.
This workflow is ideal for agile teams wanting to automate the documentation of sprint reviews or project retrospectives, ensuring consistent, insightful analysis that improves team learning and project planning.
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