Most of today's candidates are the same recycled "build a zero-employee AI agency" pitch, so this one stands out by doing something small, concrete, and genuinely useful: turning inbox chaos into a structured spreadsheet using just three Make.com modules.

The workflow is tight and worth studying as a template: Gmail watches a specific label for incoming invoice emails, Claude parses the message body and any attachments to extract structured fields (vendor, date, amount, invoice number, line items), and Google Sheets appends a new row. That's it — no vector DB, no agent framework, no fake "AI employee." Just a well-scoped LLM call sitting between two connectors it's actually good at bridging.

What makes this educational rather than promotional is the shape of the problem. Parsing invoices is the classic case where deterministic scripts fall apart (every vendor formats differently) but where an LLM absolutely shines. Watching how the prompt is structured to return clean JSON, how the Gmail label acts as a lightweight trigger filter, and how errors are handled in a four-minute build gives you a reusable pattern for dozens of similar inbox-to-database tasks: receipts, shipping notifications, form submissions, support tickets.

Bonus: it's from a channel with literally zero subscribers, so you're getting in on the ground floor of someone who's actually building instead of selling a course.