# Describe a workflow. AI builds and runs it.

**Demo** (real Slack + GitHub, button interactions):

%[https://youtu.be/fQX7MdDYKwc] 

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**Try it** without credentials at [Playground](https://zyk.dev) — 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.

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Discuss on X:

%[https://x.com/i/status/2029912393447309674] 

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**GitHub:** [https://github.com/zyk-hq/zyk,](https://github.com/zyk-hq/zyk) not released yet, self-hostable.