LLM-as-Judge Eval Design for Agentic Task Outcomes
Evaluating agents requires inspecting their full execution trace, not just their final output.
Céleste Marchand
Contributing Editor
A former academic turned practitioner, Céleste spent a decade studying feedback-driven learning systems before pivoting to editorial work covering how production AI evolves over time. She brings a rigorous, methodology-first lens to questions of iterative agent development.
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Evaluating agents requires inspecting their full execution trace, not just their final output.