Thanks, Computer

Long-term goals. Everyday decisions.

Thanks, Computer is a programmable runtime for durable, human-in-the-loop workflows. Pause an operation for a slow model, a webhook, or a human approver — for days — and resume exactly once, surviving restarts. Any language, plain JSON, every step replayable. Most workflow engines automate people out of a process; here a person — or a slow AI — is a first-class participant, not an exception.

Bundle a set of operations into a reusable stack, and curate stacks into a department — a Support department, an Invoicing department, an Onboarding department — that runs a real business function on your own data, carrying its context across emails, web requests, schedules, approvals, and AI.

Your LLM has context. Why shouldn’t your work?

What people build with it:

• a support department that drafts replies with AI and pauses for a human to approve
• qualify sales opportunities against your ideal customer profile
• prioritize customer success work around retention
• guide partnership pipelines with strategic priorities
• keep fundraising and business development efforts in context
• give AI workflows the company context behind the task

How it works

Work is broken into small steps called operations, organized into an op stack. Each operation is gated by a resonator — a trigger condition that fires only when the right kind of event passes by, and says what to do when it does:

WHEN @web.req.url.path == "/opportunity"
EXEC "https://api.example.com/enrich-opportunity"

Everything at the same step runs in parallel; each operation’s output deep-merges into the shared document, which carries the flow to the next step.

Because the event is shared external memory — not parameters threaded through call chains — humans, AI, and services can collaborate on the same work: an AI operation drafts, a human operation approves, a service operation ships, all reading and writing the same context document.

Composable by design

You can think of operations as being black boxes. They receive JSON, emit JSON, and can be written in any language. Emails, web requests, AI tool calls, and schedules all become events flowing through the same shared document.

A stack’s operations may span many systems, but its behavior remains visible:

• Visible decisions: Replay every flow step-by-step.
• The why travels with the work. Context stays attached as work moves.
• Built for waiting. Continuations let an operation suspend — for a slow model, a webhook, a human reviewer — and resume days later, exactly once, surviving restarts.
• Any language, plain JSON. Read JSON, write JSON.

Run anywhere

Self-host the open-source chassis on your own infrastructure, or let our cloud be the place to run it — managed reliability, email deliverability, and fleet scale, so your departments run like infrastructure instead of a script you babysit. The CLI txco targets either. The chassis is free and open source under the MPL-2.0 — self-host it, commercial use included.

Try it in two minutes: Quickstart

txco demo