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.
After seeing Claude Code extract and organise action items from emails in plain English, Becky tried it and built four apps in three weeks.
After seeing Claude Code extract and organise action items from emails in plain English, Becky tried it and built four apps in three weeks.
Becky watched Alex Dobrenko share his screen while he asked Claude Code, in plain English, to pull action items from his emails and organise them. She then started describing what she wanted in ordinary sentences. Her first prompt was to scrape her Substack notes into a database. Over three weeks she built four tools without writing code.
She built a YouTube quote carousel generator, a podcast packager, a channel analyser and a thumbnail analytics tool. The analytics tool covered 776 videos across 57 channels in an afternoon, against three days of manual work. She did not run the email task herself.
The post only shows the email demo being watched, not built, so there are no email setup details. Her own work was other tools, hosted on free or low-cost platforms.
Read the emails in [folder or export file path] and extract every action item, with who asked, what is needed and any deadline. Organize them into one list sorted by due date and save it as [format, e.g. HTML page or spreadsheet]. You're done when each email is accounted for; don't reply to or delete any emails.
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.