Sadegh Mahdavi developed a group-based zero-rewards mechanism for entirely incorrect proof groups in the NVIDIA-NeMo/Gym repository. This feature, implemented in Python with a focus on backend development and asynchronous programming, introduced nuanced reward semantics to the proof judge workflow. By integrating data validation and aligning the update with evolving policy requirements, Sadegh enabled the system to assign zero rewards at the group level, improving fairness and clarity in evaluation. The work required careful code integration and collaboration across teams, resulting in a more flexible environment for policy experimentation. No major bugs were addressed during this period, reflecting focused feature delivery.