GJgjkim042·Feb 24, 2026Submission
Show HN: Axon – A Kubernetes-native framework for AI coding agents
Hi HN,
I originally started this project simply to safely run autonomous coding agents (like Claude in auto-mode) in isolated environments. But as I built it, I realized the potential was much bigger than just sandboxing: it's about making a coding agent callable like a standard API, and ultimately, defining your entire development workflow as infrastructure.
Axon is a Kubernetes-native framework that abstracts the coding agent itself. By standardizing the container interface, you can seamlessly plug in Claude, Codex, Gemini, OpenCode, or your own custom images without changing your orchestration.
How it works under the hood:
The architecture relies on standard K8s CRDs (Tasks, Workspaces, TaskSpawners, and AgentConfigs).
A Task is the fundamental unit of work for a coding agent. When a Task is created, Axon spins up an ephemeral Pod with
Read the rest
a freshly cloned git workspace to execute it.
You use an AgentConfig to declaratively define the specific rules, custom skills, and MCP (Model Context Protocol) servers the agent is allowed to access during that Task.
A TaskSpawner reacts to GitHub events (like a new issue or PR) and automatically generates these Tasks on the fly.
Deterministic outputs (branch names, PR URLs, token usage) are captured directly back into the K8s resource status.
To test this, I built a fully autonomous self-development pipeline. It actively triages issues, suggests new features, finds bugs, and writes the code to fix them. It uses standard GitHub issues and PR comments as the feedback loop to guide the agents. You can see how that is wired together here: https://github.com/axon-core/axon/tree/main/self-development
The main repo is here (with demo video): https://github.com/axon-core/axon
I’d love to get your real-world feedback—especially on the CRD design, the container abstraction model, and what new features you would need to actually integrate this into your workflows.