NVIDIA publishes a reproducible agent-led RL research workflow
NVIDIA documented how a coding agent set up NeMo RL and NeMo Gym, built a visual-counting environment, trained Qwen3-VL-2B and translated an off-policy RL paper into code. The guide includes skills, checkpoints and stop rules.
Why it matters: Long-running research agents need durable objectives, measurable baselines and experiment ledgers; otherwise apparent autonomy becomes unreviewable trial and error.