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How to Build a Two-Phase Confirmation Boundary for AI Voice Actions in Tencent RTC

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A tutorial on DEV Community outlines how to prevent premature tool execution in Tencent RTC voice companion applications by introducing a two-phase action boundary. The core problem arises when a user interrupts or retracts a voice command after the AI model has already generated tool arguments, potentially causing unintended actions like posting a room message. The proposed solution enforces a strict rule: the model may only prepare an action, while a fresh, explicit user confirmation is required before any commit occurs. The architecture routes RTC audio through speech recognition, an application turn coordinator, and an LLM or Dify agent, validating proposals server-side before seeking user approval. The tutorial uses TypeScript and Tencent RTC's Conversational AI infrastructure, classifying tools by their effect — from read-only to sensitive — to determine the appropriate confirmation policy.

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How to Build a Two-Phase Confirmation Boundary for AI Voice Actions in Tencent RTC · ShortSingh