You ask
Describe the outcome
Just tell your AI agent: “When an order arrives, validate it, notify the warehouse, and retry failures.”
Automation built by your AI agent
Connect your AI agent and describe what you want automated. It builds a real, versioned workflow as a candidate — and nothing goes live unless that candidate passes its test scenarios.
Early product, actively developed
export class Workflow extends
WorkflowEntrypoint {
async run(event, step) {
await step.do("send webhook", ...)
await step.do("archive result", ...)
}
}
How it works
You ask
Just tell your AI agent: “When an order arrives, validate it, notify the warehouse, and retry failures.”
Flowbrew builds it
Flowbrew turns your request into a working automation behind the scenes. Ask for a change later, and it creates a new candidate version without touching what's already live.
Flowbrew verifies
Flowbrew runs the candidate against its test scenarios before anything changes. You approve what “working” means; Flowbrew enforces those scenarios on every subsequent change.
Why Flowbrew
Your agent builds the workflow once — it doesn't improvise in production. A generated change is a candidate — not a deployment. It must pass its test scenarios before it can replace what's live.
Build beyond the template