Describe a workflow. AI builds and runs it.
Incident Response Workflow, Described in Plain English, Deployed Live, Resolved with a Slack Button Click
Demo (real Slack + GitHub, button interactions):
* * *Try it without credentials at Playground — prompt: "Fetch all Star Wars films from the SWAPI API, ask me if I like each George Lucas film, log my answers, and summarize all my decisions at the end."
Note: the playground is just to try the core idea. The real product runs as an MCP server inside Claude. You describe and manage workflows without ever leaving your AI assistant.
We're betting on two things: MCP-ready AI as the interface for building workflows, and durable execution as the engine for making them reliable. Zyk is what happens when you combine them.
You describe a workflow in plain English through Claude. Zyk generates TypeScript and deploys it to a durable execution engine. Retries, scheduling, and error handling built in by design. The generated code lives in your repo.
The insight: LLMs already know most APIs. The missing piece was always reliability. Modern durable execution engines solve that. Put them together and two-week visual editor projects become a one-line description.
A workflow can fire on a Slack message, create a GitHub issue, post Acknowledge/Escalate buttons back to Slack, and wait hours for a human to respond, then resume and close the loop automatically. No split endpoints, no manual state management.
Discuss on X:
https://x.com/i/status/2029912393447309674
* * *GitHub: https://github.com/zyk-hq/zyk, not released yet, self-hostable.
