Brilliant paper on scaling laws for agentic RL data. It's a great paper worth reading if you are synthesizing data for agentic RL. (bookmark it) They fit scaling laws for agentic RL data along three axes: tasks, environments, and trajectories. Across model sizes, families, domains, and both PPO and GRPO, the exponents order the same way, with environments above tasks and tasks above trajectories. The environment advantage seems to come mainly from world diversity, meaning genuinely…