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Hackathon kickoff. One day. One real ticket from our backlog. You run the whole lifecycle — Specify → Generate → Comprehend — while an agent does the typing.
Five labs.
Six short talks. One sandwich.
Timeboxes are hard. Done-when beats done-everything — whatever state your lab is in when time runs out, that's what we debrief.
Metaphor: Dan Shipper, Every's podcast AI & I, with Kieran Klaassen. The Specify → Generate → Comprehend framing is this engagement's own adaptation.
Your time moves to the two ends.
You write less and less code. The time does not vanish — it moves to the two human ends.
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Vague in, vague out — judgment goes in here, while changing your mind is still cheap. Unclear requirements are this company's single biggest source of delay. This block is the antidote.
Claude Code in the terminal.
Your tool for the day: a session, your repo, and control over what it may do.
- Start it in the repo root. Now it can see your real code.
- Permissions. It asks before acting, until you choose to let it run.
- Plain language. Point at real files. No magic words.
- Esc interrupts. At any time. You are always the one in charge.
Plan & grill.
Your ticket becomes a plan so clear someone else could build it.
That was the agentic loop.
It read, it ran, it looked at the result, and it went again. That loop is the difference between an agent and a chatbot.
- Each step is a tool call. The result decides the next step.
- It acts — it doesn't just answer. That's what makes it wave 2.
- The loop stops when the goal is met, or when it needs you.
Someone just hit the dumb zone.
Long session, many files — and the answers went vague. The context window is nearly full. The agent's short-term memory has a hard limit: old details fall off, or blur. This is normal. Now you know its name.
The factory is many sandwiches at once.
Many agents work at the same time. But only one person reviews. That is the slow part.
Today was the whole sandwich, fast. The next sessions slow it down.
Each session takes one station you ran today and builds it properly — with homework on real tickets in between.
Everyone drove an agent through Specify → Generate → Comprehend on our own code — and the lessons you wrote into CLAUDE.md are still here tomorrow. That loop, repeated, is the factory.
The harder parts — many agents at once, autonomous routines, real review at volume — come in the next sessions. We are not learning a tool. We are building a factory the team owns. Today was day one.