How We Benchmark Deep Agents
The article discusses the development of a robust evaluation framework for Deep Agents, an open-source agent harness, to assess the performance of various agent tasks. It outlines three benchmarks—Harbor-Index, π³-bench, and ContextBench—each focusing on different types of agent work, such as autonomous tasks, conversation, and retrieval. The evaluation process uses Harbor, an open-source framework, to run end-to-end tests, emphasizing the importance of environments and artifacts in agent performance. The benchmarks are designed to help iterate efficiently, with a "lite" version for quick testing and a full version for final decisions, while also including unit tests to validate harness behaviors.
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