Coding AI agents are becoming practical operators for long-running machine learning (ML) workflows. They can inspect repositories, set up runtimes, resolve build issues, launch experiments, monitor execution, analyze metrics, and summarize results. For reinforcement learning (RL) research, this matters because meaningful metrics often appear only after the essential experiment infrastructure is in place. Autoresearch is … Continue reading How to Run an Autoresearch Workflow with RL Agent Skills and NVIDIA NeMo