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