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.
Poster built a system that runs their whole business through Claude Code instead of Claude.ai; the specific tasks aren't detailed in the snippet.
Poster built a system that runs their whole business through Claude Code instead of Claude.ai; the specific tasks aren't detailed in the snippet.
The poster says they replaced the Claude web app with Claude Code in the terminal and built a setup where Claude became “infrastructure” for the business rather than a chat tool. In the thread, they add that they still use Claude.ai for creative and design work, while Claude Code handles infrastructure and execution, with the two connected; commenters also discuss reviewing commands, permissions, and error handling as human checkpoints.
The source gives no business KPIs or task-by-task breakdown, so the main result stated is the workflow shift: they say they now run the business through Claude Code instead of Claude.ai. The thread’s clearest limitation is safety, with commenters warning against broad system permissions and stressing review and rollback.
Useful catch: even the poster says Claude.ai still does the creative/design side, so this was not a full one-tool replacement.
I run [type of business]. Set up a project folder with a notes file describing my business, customers, tools and recurring tasks. Then handle this week's tasks: [list 2-3 tasks such as invoicing summaries, customer replies, reports]. Finish with each task's output saved as a file and a short summary of what you did. Don't send emails, make payments or delete files without showing me first and getting my approval.
An n8n and Gemini agent receives patient chat messages, keeps context, uses clinic info from Google Sheets and responds to enquiries.
An n8n workflow has AI classify web-form jobs by type, urgency and summary, create an Airtable record, reply instantly and flag uncertain cases.
Lindy agents summarized meeting notes, sent action items to teammates, suggested knowledge-base replies on support tickets, and handled follow-up emails and calendar updates.