Agentic Orchestration Policy: Asynchronous Reasoning and Control for Embodied Coding Agents

Coding agents can construct and revise robot behavior during execution, but their deliberation takes time. A single reasoning process can delay work that different robot components could perform independently. We introduce Agentic Orchestration Policy (AOP), an asynchronous framework of persistent coding agents that reason and act for configurable robot control groups. A hyper-agent coordinates their work, deciding what to delegate, which actions must wait for others, and when to control coupled groups directly. This lets local work progress concurrently while coordination adapts to physical dependencies. Across 72 real-world rollouts in 25 task/platform settings, reduces task-balanced time cost relative to Direct Policy in all three categories: Fully Parallel, Parallel-Sequential, and Collaborative, with a 28.2% reduction overall. On Collaborative tasks, it also has lowers mean time cost than a fixed robot arm assignment, which we call fixed delegation. Case studies show how members prepare actions in parallel and how fixed delegation can delay shared actions through repeated planning and waiting. We will release the framework code and a rollout dataset containing observations, generated programs, actions and feedback to support research on how coding agents reason and act in the physical world.