AssemblyAI argues that spec-first coding agents can build and maintain voice agents more flexibly than point-and-click builders.

AssemblyAI said a coding-agent workflow gives developers more control than a visual builder when creating voice agents, arguing that plain-language instructions translated into code can scale beyond the limits of a form-based interface. In a blog post published Friday, October 30, 2026, the company said the approach is better both during development and after deployment because it keeps the system’s behavior in code the team can version, test and change.

The post contrasts two build paths. Visual builders, it says, let users configure an agent through fields and dropdowns, which can make a first build easier but can also cap what the platform exposes. AssemblyAI’s alternative is to describe the agent to a coding agent such as Claude Code, Cursor, GitHub Copilot or Windsurf, then have it generate and modify the project directly against three APIs: streaming speech-to-text with Universal-3.6 Pro Realtime, an LLM through LLM Gateway, and AssemblyAI Text-to-Speech.

AssemblyAI framed the technical case around a cascaded voice stack in which the agent transcribes speech, decides what to say, and then speaks. The company said that structure works well with coding agents because each hop has a narrow documented contract: speech-to-text emits events such as Begin, Turn and Termination; LLM Gateway is OpenAI-compatible; and text-to-speech uses methods including generate(), flush() and cancel(). The post said separating the hops also makes it easier to test each layer independently before wiring them together.

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