Build long-horizon RL environments and tasks for agent training, spanning many steps and hours of realistic effort rather than single-shot prompts Shape environments end to end: stateful, resumable systems with snapshotting, checkpointing, and branching rollouts, at multi-node scale where needed Generate and refine ideas for tasks and agentic trajectories across multi-turn, tool-using, and computer-use agent loops with persistent state across turns Design reward structure for sparse-reward sett…
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