AI Agent Evaluation Harness
An AI agent evaluation harness is the testing infrastructure built specifically to assess an autonomous AI agent's performance across a suite of tasks — measuring success rate, efficiency, and safety of its actions — accounting for the fact that an agent's exact path to a goal can vary between runs.
Unlike testing a single LLM response, evaluating an agent means assessing an entire multi-step trajectory — did it complete the task, how many steps did it take, did it use tools correctly, did it ever attempt an unsafe or out-of-scope action along the way — not just whether the final output looked right.
Because agents are non-deterministic by nature, a solid evaluation harness typically runs each task multiple times and reports success rate and consistency across attempts, rather than treating a single pass or fail as representative — an agent that succeeds 60% of the time on a task needs a very different confidence assessment than one that succeeds consistently.
