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You are evaluating an AI agent that can take multiple valid paths to complete the same task, and its outputs vary across runs. The team wants a framework that can judge quality fairly, compare versions, and catch regressions without assuming deterministic behavior.
How do you design an evaluation framework for non-deterministic AI agents?
