Every AI agent stops improving the moment you stop improving it. Not because the models stop getting better. Because new workflows, architectures and engineering tricks never reach your agent on their own.
They're buried inside thousands of GitHub repositories. Somewhere, there's already a workflow your agent has never seen. Finding it is still a human job.
Open the repository. Read the code. Figure out what's actually new. Decide whether it's worth keeping. Then teach the agent manually.
That never made sense to me.
If an AI can write code, review pull requests and use tools, why can't it discover new skills by itself?
So I built a system that does exactly that. It continuously scans GitHub, extracts reusable workflows, converts them into Agent Skills and expands its own capabilities without waiting for a human to update it.
https://x.com/rvaniaaaa/status/2075975822461084061


