Loop Design: The Anthropic Playbook for Agentic Systems

Most practitioners still operate large language model agents the way they operated chatbots: one prompt, one reply, a human in the loop on every turn. We argue this is a transitional posture, not an endpoint. As agents acquire the ability to discover their own work, isolate their changes, and check each other, the unit of engineering shifts from the prompt to the loop: a scheduled, self-driving cycle that the operator designs once and supervises rarely. We present a field playbook for designing such loops. We decompose a loop into five movements, Discovery, Handoff, Verification, Persistence, and Scheduling, and define five levels of operator autonomy from manual prompting to fully autonomous operation. We give a structural account of why an agent that grades its own work tends to inflate its score, and why an independent verifier, the “thing that can say no,” is the single highest-leverage component in the design. We close with a fourteen-step adoption path and a set of failure modes observed in practice. The central claim is simple: you stop prompting the agent, and start building the system that prompts it.