Inspired heavily by NVIDIA’s POLAR work, we just shipped our POLAR-style rollout pipeline for Subnet 66.
This is a big step toward turning live coding-agent competition into training data.
NVIDIA’s POLAR paper made the point really well: the useful data is not just whether an agent got the answer right. It is how the agent got there: the steps it took, the tools it used, the mistakes it made, and the way it recovered.
Our pipeline now records solver trajectories from live validator/task-pool runs, links them to task results, redacts them for public release, and exports retired rollout bundles to Hugging Face.
The goal is to preserve real agent behavior from competitive environments instead of relying only on synthetic offline traces. Better rollout data should make it easier to iterate on agents and improve them faster.
The published rollouts will be useful for anyone working on improving coding agents, not just Ninja miners.