How to evaluate voice agents: execution, outcomes, and experience

Building effective voice agents involves ensuring they feel natural, resolve user issues, and achieve intended business outcomes. Evaluations across execution, outcome, and experience are crucial to identify weaknesses and measure improvements. Execution focuses on whether the agent follows instructions accurately, using deterministic evaluators and LLM judges for semantic requirements. Outcome assessments determine if interactions achieve their goals, highlighting instruction adherence versus outcome effectiveness. Experience evaluations consider responsiveness, naturalness, and conversational friction, using latency measures and audio-aware LLM judges. LangSmith supports these evaluations by tracing interactions, scoring conversations, and providing tools for continuous improvement and human review. It emphasizes the importance of evaluating each dimension separately to understand agent effectiveness comprehensively.

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