What Voice AI Teams Can Learn from Hamel Husain: Beyond Vibe-Checks to Data-Driven Voice AI QA
Blog post from Coval
In a recent episode of Conversations in Conversational AI, Hamel Husain emphasized the critical role of evaluation in the development of voice AI products, arguing that evaluations should be integrated into the development lifecycle from the start rather than being treated as an afterthought. Husain, a leading expert on AI evaluation, highlighted that a significant portion of development time, ideally 60-80%, should focus on testing and evaluating voice AI systems to ensure their effectiveness in real-world scenarios. He advocated for a process that begins with error analysis of real conversation data before moving on to automated testing, thus allowing teams to identify and fix issues that impact business outcomes. This approach requires an organizational shift across teams, involving product managers, operations, and engineering, to prioritize conversation success rates and failure mode prioritization. As voice AI technology advances, particularly with the recent viability of agentic voice systems, systematic evaluation becomes indispensable for ensuring quality and reliability, making it vital for companies to adopt evaluation-driven development practices.
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