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Don't Trust Your AI Agents. Test Them Like a Scientist — Stephanie Jarmak, Omni Analytics
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Fusion42 · 24 October 2026 · Fusion42 review
Stephanie Jarmak of Omni Analytics explains that AI agent evaluations must be conducted within the specific context and workloads of the deploying environment, warning that standard public benchmarks can mislead by shifting model rankings significantly. She advocates for building internal, real-workload benchmarks and detailed debugging methods to ensure AI agents perform reliably in production.
This Wire brief sits within Fusion42's coverage of AI Agents and MLOps.
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You must calibrate AI agent tests to your real workflows to avoid false confidence. Running your own benchmarks and fully tracing agent use will protect you from costly deployment failures.
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1 source · 23 Oct 2026
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