A Harness for Every Task: Putting a Team of Claudes on One Job

Large language models often fail at complex, long-horizon tasks due to issues like goal drift, agentic laziness, and self-preferential bias. Anthropic's "Dynamic Workflows" address this by having the AI, like Claude, write a custom JavaScript program or "harness" for the specific task. This approach moves the overall plan out of the model's volatile context window and into a persistent script. The harness then orchestrates multiple, fresh-context AI agents to perform discrete steps, such as generation and review, ensuring the original goal is not lost and the work is completed reliably.