The AI voice agent space is drowning in noise. 10,000+ LinkedIn posts a month, almost none showing architecture. This talk draws a hard line between demo-grade and carrier-grade.
I'll walk through SignalWire's three-layer AI Agent control plane -- typed functions, state machines, and prompts -- and why collapsing them into a single system prompt is the root cause of every production failure nobody posts about. I'll introduce Programmatic Governed Inference (PGI), the architectural principle that separates code-driven business decisions from AI-driven conversational decisions, and show a concrete PGI technique: zero-argument tool calls that read from validated stored state instead of letting the LLM re-supply data on every call. Fewer arguments, fewer failures, guaranteed consistency.
Everything shown is open source at github.com/signalwire. No demos, no happy-path videos. Just architecture, code, and the failure modes the industry skips.