Answer patient enquiries for a clinic by chat
An n8n and Gemini agent receives patient chat messages, keeps context, uses clinic info from Google Sheets and responds to enquiries.
A PM has Claude Cowork read completed Linear tickets, pick what matters, draft the update and suggest email or in-app format, replacing about an hour per sprint.
A PM has Claude Cowork read completed Linear tickets, pick what matters, draft the update and suggest email or in-app format, replacing about an hour per sprint.
The PM set up a recurring Claude Cowork task that runs every two weeks. Through MCP connections, Claude reads completed Linear issues, decides which ones are user-facing, drafts changelog copy from ticket descriptions and comments, publishes it, and then chooses whether the release also merits an email and in-app notification; the PM says they usually just review and send it.
It replaced about an hour of manual work each sprint, and the PM says the writing is better because Claude includes details they used to skip. They still review it before shipping, but say that happens 90% of the time rather than writing it themselves.
The key catch is the MCP setup: Claude needed one connection to Linear and another to the publishing destination, plus rules for when bigger updates should trigger email and in-app announcements.
Read the tickets completed in [Linear project or team] during [sprint dates]. Pick the changes customers would care about, skip internal chores, and draft a changelog in plain language. Finished means one draft in [email or in-app] format plus a short note on why you left certain tickets out. Show me the draft before sending or posting anything.
An n8n and Gemini agent receives patient chat messages, keeps context, uses clinic info from Google Sheets and responds to enquiries.
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