The FestPass AI workflow simulator: a seven-node agent crew — Grace the greeter, Marcus the profiler, Ava on knowledge retrieval, Daniel on compliance, Maya interviewing, Theo inspecting and Zara on experience — above an activity log and a shared clipboard holding the run's state, one field per row.

Part I · Chapter 9

Ship It Live

A live deploy failed on a wrong start command, and was fixed on stage.

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Day thirteen was the deploy. FastAPI to GitHub to Render, live, in front of the cohort.

It failed.

My repo failed, said Nicole Johnson, the Python lead, in the middle of it. Then, having found it: your start command is important.

The command was wrong. That is all it was — the kind of error that produces a wall of red output and tells you almost nothing about the actual cause, and which every engineer who has ever deployed anything has lost an afternoon to. She found it in front of everyone, fixed it in front of everyone, and said the line the day is remembered for: my little bot is online. And it is ready to go.

The teaching value of that failure exceeded the teaching value of a clean deploy by some distance. A demonstration that works shows you a happy path. A demonstration that breaks and is repaired shows you what the work actually consists of — which is mostly this, and which is survivable.

Chief Judge Farrell said much the same thing from the stage at the showcase, three weeks later: technical setbacks are standard, and feedback is fuel. By then several teams had already lived it.