Don't Trust Your AI Agents. Test Them Like a Scientist — Stephanie Jarmak, Omni Analytics
Stephanie Jarmak, a former astronomer who now builds evals at Omni Analytics after building a large coding benchmark at Sourcegraph, argues that most agent evaluations are easy to misread.
She shows how swapping only the harness moved results by 30%, why public benchmarks are for shortlisting rather than decisions, and how to design your own evals like an experiment: realistic tasks, repeated runs, full traces and a measurement that matches what you care about. She also covers quality gates that actually stop work, the human review bottleneck, agent records you can't trust, and why production is the final test. Chapters: - 00:00 Intro - 01:11 When the agent ignores your tool - 02:47 The harness changes the results - 03:51 Public benchmarks vs.
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