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.
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?