Show HN: Kelos – Define your AI coding agent workflow as YAML on Kubernetes (github.com)

4 points by gjkim042 4mo ago ↗ HN

Kelos is a Kubernetes framework for orchestrating autonomous AI coding agents (like Claude Code) in ephemeral pods.

The original goal was sandboxing — I didn't want to run agents with --dangerously-skip-permissions locally. But the real unlock turned out to be declarative workflows. You define agent tasks as Kubernetes CRDs, things like:

- Watch for "bug" issues → auto-draft a fix PR

- Auto-review incoming pull requests

- Auto-triage new issues with labels and priority

- Periodically scan the codebase → propose improvements

- Test the project as a new user → surface rough edges

Self-development pipeline: https://github.com/kelos-dev/kelos/tree/main/self-developmen...

I've been using Kelos to develop Kelos. When something breaks, I refine the YAML or add features to the controller. It's early and rough around the edges, but the core loop works.

Happy to answer questions about the design or what's broken.

3 comments

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[dead] jlongo78 4mo ago ↗

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gjkim042 4mo ago ↗

Thanks,

Actually, Kelos captures structured outputs after each coding task compeletes: the final branch, the created PR link if exists, input/output tokens, and so on. And coding agent’s logs would remain after finished as a container log.

Is theere anything you want to add additionally?

mrgaro 4mo ago ↗

I'm an avid user of the Claude Code planning feature and I like how Claude Code asks for questions. I also often iterate the plan before finally giving it a go.

How do you solve this in Kelos?

I tried to check the code base, but it didn't really provide any glues. I guess I could instruct the agent to build a plan and to post the plan in the issue and then iterate that with written comments in the issue. Is that how you run it?