here's my [similar take](https://github.com/testeranto-dev/testeranto)
I didn't want to be on the hook for supporting an open source version though, so never made it public. Good on you for putting it out there.
A few differences I can quickly spot, fwiw...
I went with Firestore over Postgres for the lower cost, and use Cloud Tasks for "free" deduping of webhooks. Each webhooks is validated, translated, and created as an instant Cloud Task. They get deduped by ID.
We see a lot of value in a scheduler. So running a prompt on a schedule - good for things like status reports, or auto log reading/debug.
I prefer to put my PEMs in to KMS instead of Secret Manager. You can still sign things but without having to expose the actual private key where it can be snooped on.
I run the actual jobs on spot VMs using an image baked by Packer with all the tooling needed. You don't run in to time/resource limits running them as Cloud Run jobs?
Too real. We’re currently still sticking to local agent workflows which feel more powerful than cloud native ones. Moving that to your own cloud with no third-party control plane feels like the right middle ground. Nice work
EDIT: the adversarial two-agent review loop is really clever!
However I feel it will be an uphill battle competing with OpenAI and Anthropic, I doubt your harness can be better since they see so much traffic through theirs.
So this is for those who care about the harness running on their own infra? Not sure why anyone would since the LLM call means you are sending your code to the lab anyway.
Sorry I don’t want to sound negative, I am just trying to understand the market for this.
Good luck!
On a separate note, READMEs written by AI are unpleasant to read. It would be great if they were written by a human for humans.
Also agree that teams should invest in their own harness (or maybe pedantically, build a system on top of harness likes Claude Code, Codex, Pi, or OpenCode)
It worked great but time to first token was slow and multi repo PRs took very long to create (30+ mins)
Now im working on my standalone implementation for cloud native agents