System Prompt Design for Voice Agents [Testμ 2026]

Amanda Martin’s Testμ Conf 2026 session examined how system-prompt design can substantially affect voice-agent reliability, efficiency, and caller experience, using three restaurant-booking agents with identical models, tools, and test scripts but different prompts. A personality-focused prompt produced a pleasant call but failed to confirm critical details, while a rigid numbered prompt caused the agent to narrate its procedure and create an overly long, impractical conversation. A structured best-practices prompt combining personality, knowledge, state and ambiguity handling, workflow and tool rules, examples, and recovery instructions was the only one to clarify the ambiguous phrase “next Friday,” while also delivering the best quality and shortest calls. Martin recommended evaluating agents through a layered process of manual demos, chat simulations for tool sequencing, and full voice simulations for interruptions and turn-taking, with atomic pass-fail criteria and additional deterministic transcript checks where risk warrants. She also emphasized that model selection and platform settings are central to handling accents, multilingual conversations, and overlapping speech, while prompts can support these capabilities through pronunciation examples and clear operational boundaries.

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