Your Voice Agents Need Tests. Now They Have Them.

Voice agent developers often face challenges when changes to prompts or tools result in silent regressions that aren't immediately detectable, impacting performance metrics over time. To address this, a new testing method called "Evals" has been introduced, which allows developers to write tests for voice agents similar to unit tests for code. Evals involve defining JSON conversations with specific criteria for each assistant interaction, enabling developers to ensure that the assistant performs expected actions, such as calling the right tools or asking necessary questions. This method supports different judging strategies, including exact matching for deterministic behaviors and LLM-as-judge for subjective evaluations like tone and policy adherence, providing a comprehensive testing framework that aligns with continuous integration and deployment pipelines. By turning past production issues into tests, Evals help prevent future regressions, making voice agents more reliable and consistent as they evolve. The approach empowers developers with confidence in their deployments, offering a structured way to maintain and improve the performance of voice agents over time.