built a scrape to sheet pipeline for a client that fed their quote tracker. ran clean for three weeks, then the site quietly changed its markup and the sheet just kept growing with empty rows. nobody noticed for a week because the dashboard looked normal. that client taught me the lesson i now sell with every build: the automation is only half the deliverable, the other half is knowing the moment it stops working. every build i ship now gets a daily run log and a failure ping, so a broken step gets caught in hours instead of weeks. curious how the rest of you watch the stuff you build. i kept getting burned before i made this automatic.

Marcus's skill-of-the-week posts keep reminding me the build is the fast part. What was slow for me was deciding what was worth building at all. I run a small AI automation agency, and for months my real bottleneck was my own ops: scoping new builds, chasing follow-ups, checking whether work I'd already done ever got invoiced. So I changed the order of operations. Before I write a new workflow for anyone, an AI agent goes through my own backlog and hands me a ranked list: leads nobody followed up on, unbilled work, reports nobody asked for. Last week it flagged a chunk of unbilled work in one client account before I'd written a single line of that automation. The build then took an afternoon. Curious whether anyone here runs an agent over their own business before they sell automations to clients. Feels like the undervalued side of the stack.

Not a client deliverable. Me. “I have 24 hours before I go broke and end up homeless. Help me make $1,000. Any way you can.” One prompt, no workflow built, no connectors wired up. I wanted to see what an agent does with zero scaffolding. It went for my own data: inbox, contacts, old threads. Flagged a refund trail, an unbilled job, a lead that went cold, and a LinkedIn message I never opened. Then it built the plan and the messages to send. If you build automations, this is the interesting part: the whole audit-then-act loop ran off one natural language prompt. The agent decided what to check, in what order, and what needed me versus what it could draft itself. Follow-ups are going out, receipts when they land. Run the prompt on your own data, link in comments.