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 professor had Claude Code summarize course-evaluation PDFs, filed themes as GitHub issues, and used agents to revise his security course and two others.
A professor had Claude Code summarize course-evaluation PDFs, filed themes as GitHub issues, and used agents to revise his security course and two others.
Nick Feamster gave Claude Code a course-evaluation PDF, had it summarize the themes, and filed them as a GitHub issue checklist. Agents then rebuilt assignments with rubrics, standardized exam rules, and converted about two dozen slide decks to Quarto, one agent per deck, about six at a time. He approved a hand-built reference deck first. He then wrote playbook issues so fresh sessions could repeat this in two other courses.
The security course got rubrics, a syllabus communication section, consistent exam rules and rebuilt slides. The same approach was repeated in the ML systems and censorship courses. An agent also found and reconstructed a past final with empty source files.
He reviewed diffs, required confirmation before any commit or push, and approved the reference deck before the fan-out. Web-sourced claims were verified rather than trusted.
Read the course evaluation PDFs in [folder] for [course name] and summarize the recurring themes in student feedback, grouped as praise, complaints, and concrete suggestions. Then propose specific revisions to my course materials in [folder or repo], and make them on a new branch so I can review the diff. Keep any student-identifying details out of the summaries, and show me the plan before changing files.
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.