AI · Technology · 2026-09-09 10:05:00
When developers first work on harness engineering for agentic coding systems, they often run end-to-end benchmarks like Terminal-Bench and DeepSWE, see composite scores move slightly, and don't know why. Behavioral evaluations better measure whether expected behaviors actually occur and whether changes move in the right direction. They function like integration tests for improving agent harness operation, asserting on intermediate execution steps such as specific tool calls or file modifications instead of final string equality. A rich behavioral eval set provides a baseline for iterative prompt improvement.
Source: developers.googleblog.com
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