I Built a Multi-Agent AI Runtime in Go Because Python Wasn't an Option

The idea that started everything Some weeks ago, I was thinking about Infrastructure as Code. The reason IaC became so widely adopted is not because it's technically superior to clicking through a cloud console. It's because it removed the barrier between intent and execution. You write what you want, not how to do it. A DevOps engineer doesn't need to understand the internals of how an EC2 instance is provisioned — they write a YAML file, and the machine figures it out. I started wondering: why doesn't this exist for AI agents? If I want to run a multi-agent workflow today, I have two choices. I learn Python and use LangGraph or CrewAI, or I build my own tooling from scratch. Neither option is satisfying. The first forces me into an ecosystem and a language I might not want. The second means rebuilding primitives every time. What if I could write a YAML file that described what I wanted — which agents, which tools, which LLM providers — and a runtime would just handle the rest? What i