What it is
I built Biscuit to see what an AI agent really changes when it works on Kubernetes. It gives a coding agent a broken k3s task on a disposable VM. I compare the final cluster state with an independent check and keep the run evidence.
How it works
I roll a Proxmox VM back to a clean snapshot before each trial. The agent runs commands over SSH while the runner records what it did and what changed. A separate verifier checks the task result. I save the trajectory, audit evidence and cost, then reset the VM.
Flow
- Clean Proxmox snapshot
- Broken k3s task
- Agent commands over SSH
- Independent verification
- Evidence and reset
The problem
The first full receipt path slowed short commands because it gathered cluster inventories around each command. I saw this in paired timing runs and traced much of the cost to those inventories. A hooks only run was still slow, so the tracer alone did not explain it. I moved to persistent collection and returned bounded receipts with command output. I kept failed attempts in the record.