Cowork automates sprint changelog generation using Claude AI and MCP connections

Automating sprint changelogs with Cowork and Claude

A project manager has automated their most tedious recurring task: creating end-of-sprint changelogs. Previously, this required manually sifting through completed Linear tickets, deciding what to include, writing copy in ChatGPT, publishing it, and determining whether updates warranted email or in-app notifications.

How the automation works

The Cowork task runs every two weeks automatically and performs these steps:

• Claude connects to Linear via MCP (Model Context Protocol)
• Pulls completed issues from the sprint
• Identifies which issues are user-facing
• Writes changelog copy using actual ticket context including descriptions and comments
• Publishes the changelog through another MCP connection
• Triggers email and in-app notifications for significant updates
• Quietly adds smaller changes to the changelog page

Results and observations

The PM reports that Claude's generated copy is "genuinely better" than their manual work because it pulls details from ticket descriptions and comments that they would have skipped when rushing. They now spend about 90% of their time just reviewing and shipping the changelog rather than creating it from scratch.

The only remaining manual task is creating the header image, which takes about 2 minutes using a screenshot beautifier tool.

Recurring automation use case

The PM notes that Cowork is "undersold as a scheduling tool" and that while most use cases focus on one-off tasks, the real value comes from automating recurring work. This includes "the boring work that eats an hour every week or every sprint that you never get around to automating because writing a script feels like overkill."

Instead of writing scripts, users can describe what they want in plain English and schedule it to run automatically.