I'm a student learning AI integration and automation by building one real workflow every day for 60 days. Everything gets documented and pushed to GitHub.
**
Today's build: Automated Client Reporting System**
Built a workflow that writes and delivers professional weekly performance reports to every active client, every Monday at 7am, automatically, forever.
What I learned: Getting Claude to write consistent, structured narrative reports across different client datasets is a prompt engineering challenge, not just an API call. Tone, section structure, and handling flat or missing data without hallucinating trends all needed explicit instructions.
The loop logic hit different too — one mapping error and the wrong client gets the wrong report. Zero margin for error.
How it works:
Schedu
le trigger fires every Monday 7am
Airtable returns active client list
Loop pulls each client's metrics from Google Sheets
Claude writes a 5-section narrative report per client
Google Doc created → Gmail delivers to client → Airtable logs it
Biggest lesson: Test with dummy data obsessively before anything touches real client data.
Stack: n8n · Claude API · Google Sheets · Google Docs · Gmail · Airtable
🔗 https://github.com/mbuguacessy-glitch/automated-client-reporting
58 builds to go 💪
Top comments (0)