Chat history is not a work record
You ask your AI to plan the week. It gives you a beautiful answer. You ask it to book the thing, draft the email, do the research. It does — mostly.
Then what?
The work disappears into a scroll of messages. Three days later you can't answer the basic questions: What did it actually finish? What did it skip? What were the steps? Could it do the same thing again next month, the same way?
Chat is a great way to ask for work. It is a terrible place to keep work.
Engineers already solved this
Software teams don't run operations out of a chat log. They have runbooks (the steps, written down), runs (this execution, on this date), and audit trails (what happened, when, by whom, with proof).
Developers get this from Linear, GitHub, and CI. Everyday task tools can now let an AI read or update tasks, but access is not the same as a durable run. The person using AI for meal planning, travel booking, home admin, or a small business still needs the steps, output, and handoff in one place.
That's what OnlyCheckboxes is: runbooks, runs, and audit trails, wearing checkbox clothing.
The simplest shared surface
A checklist is the smallest structure that both a human and an agent can work:
- What needs doing — the item, with enough context to act on
- Who or what owns it — you, or your agent
- When it matters — today, Friday, every week
- Whether it got done — the box, checked, with proof attached
Your agent connects over MCP. Tell it "plan my week" and real checklists appear — not a wall of chat. Save any checklist as a template and it becomes a repeatable runbook your agent can instantiate as a fresh run. When the agent finishes a step, it checks the box and attaches the output. Every completed box is a receipt.
The point is not merely that an AI can update the list. The point is that the list preserves how the work ran and what came back.
You're managing checklists anyway
Everyone already keeps lists somewhere: an app, a notes file, a whiteboard, their head. The question is whether that list is a dead end or a surface your agents can pick up.
If an AI does some of your work — and increasingly, it does — you need a list it can read, run, and check off. That's the whole product.
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