A Taxonomy of RL Environments for LLM Agents Model architecture gets all the attention. Post-training recipes follow close behind. The reinforcement learning (RL) environment — what the model actually practices on, how its work gets judged, what tools it can use — barely enters the conversation. That’s the part that actually determines what the agent can learn to do. A model trained only on single...