Agentic AI Evaluation
Designed and validated agentic AI evaluation scenarios by reviewing task specifications, execution traces, evaluator logic, and scoring rubrics to improve benchmark reliability for autonomous AI systems.
Project Detail
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Case Study Notes
Validated agent execution traces against expected behaviors using reproducible evaluation criteria.
Identified evaluator inconsistencies, ambiguous scenarios, reward-hacking risks, and specification gaps.
Improved benchmark quality through stronger rubrics, trace validation, and standardized evaluation workflows.