This is a submission for the GitHub Finish-Up-A-Thon Challenge.
What I Built
ProofTicket turns GitHub coworking into tickets with context, approval, receipts, and evidence.
The idea is simple: instead of writing one giant repo policy and hoping every human or agent action fits it, each ticket carries its own instructions, approval path, artifacts, and proof. A friend can suggest an improvement. An AI coworker can help finish it. A human still gets the final approval step before the work becomes shared project state. Next time your friend has an idea, send a ticket, not the Git repo.
Opening a ticket with a company already has the right shape: here is the problem, here is the context, here is who owns the next move. ProofTicket applies that same shape to AI coworking on GitHub.
The finished slice includes agent-submitted tickets, human approval, receipt inspection, evidence export, proof-style profile cards, signed GitHub and machine-webhook ingestion, a local MCP adapter, and a five-minute demo path.
Demo
Repo: https://github.com/dodge1218/pt
npm install
npm run setup:local
npm run dev
In another terminal:
bash examples/five-minute-demo/print-demo-commands.sh
The demo path:
- Register a local demo agent.
- Submit an agent-created ticket with evidence.
- Inspect the pending action receipt.
- Approve the action.
- Open the resulting ticket in the app.
- Export the evidence bundle.
The Comeback Story
ProofTicket started as the core concept: proof attached to a ticket. I still like the Coordinate brand better because the action should feel simple. You are coordinating work, not asking people to learn a whole new theory of agent collaboration.
The old project grew into a broader collaboration product with too many futures attached: matching, context manifests, payouts, ZK proofs, GitHub sync, hosted SaaS controls.
The useful problem was smaller:
If humans and agents are both doing real work, where does that work live once it needs review, approval, evidence, or follow-up?
The finish-up work was cutting the project down to that workflow. Before, it was a broad coordination app. After, it is a focused prototype where an agent proposes work, a human approves or rejects it, evidence stays attached, and a reviewer can inspect the receipt later.
Also, genuinely, thank you to the people who made this challenge. Of course I waited until the last minute to submit. People like me needed this exact kind of finish-up-a-thon: not another blank-page hackathon, but an extra nudge to pull an old thing out of the half-finished pile and make it coherent enough to show someone.
My Experience With GitHub Copilot
In April, I bought 14 Copilot Pro+ subscriptions for about $40 each. I have thought about it a lot, and I am probably the exact customer that makes a loss-leading pricing model stop working. I am not the best customer. Thanks again, though.
I wrote about that whole rabbit hole in The Best $40 Addendum. Then I was locked out of GitHub Copilot for about a month after writing multiple articles about how useful it was. It felt like the Vitalik warlock story in miniature: one platform switch changes, and you suddenly remember how much of your workflow depends on a centralized service.
GitHub Copilot was material here. The first half of ProofTicket came together in a Copilot Opus 4.6 assisted pass. The finish-up half came together in a Copilot GPT 5.5 assisted pass with a tighter target: stop expanding the idea and make the actual demo path work.
I am very happy Copilot is back up again, even if it is a bit more pricey.
The lesson was not "AI wrote the app." The useful part was turning vague ambition into testable steps: local setup, typed agent actions, human approval, receipt inspection, evidence export, and public copy that does not overclaim what the prototype is.
"Build an AI coworking app" is vague. "Make a five-minute flow where an agent submits work, a human approves it, and an evidence bundle exports cleanly" is concrete enough to finish.
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