I've been building Hector, a declarative AI agent platform in Go that uses the A2A protocol. The idea is pretty simple: instead of writing code to build agents, you just define everything in YAML.
Want to create an agent? Write a YAML file with the prompt, reasoning strategy, tools, and you're done. No Python, no SDKs, no complex setup. It's like infrastructure as code but for AI agents.
The cool part is that since it's built on A2A (Agent-to-Agent protocol), agents can talk to each other seamlessly. You can mix local agents with remote ones, or have agents from different systems work together. It's kind of like Docker for AI agents.
I built this because I got tired of the complexity in current agent frameworks. Most require you to write a bunch of boilerplate code just to get started. With Hector, you focus on the logic, not the plumbing.
It's still in alpha, but the core stuff works. I'd love to get feedback from anyone working on agentic systems or multi-agent coordination. What pain points do you see in current approaches?
Repo: https://github.com/kadirpekel/hector
Would appreciate any thoughts or feedback!