Prompting Claude to build voice agents

Building effective voice agents using AI models such as Claude involves more than just generating code; it requires a strategic approach to context and documentation. The process starts with grounding the AI in current API documentation to prevent outdated code issues, as seen with fast-evolving APIs like AssemblyAI. It's crucial to separate the engineering and business logic prompts, initially focusing on the technical setup before layering in business-specific details. Utilizing real call transcripts instead of hypothetical scenarios enables the AI to understand actual user interactions, which enhances the system prompt, key terms, and tools based on real data. The choice between AI models like Claude and Codex is less critical than ensuring access to up-to-date documentation and real conversational data, as these factors are pivotal in developing a voice agent that is accurate and reliable.