5 lessons from talking to 100+ teams building voice AI agents
Real-time voice AI is young, and the tools and infrastructure that will power its future are being built right now.
After working with and speaking to hundreds of teams building voice AI agents, we’ve learned a lot.
Some of the most important things:
Voice AI demos are easy. Scaling to production is hard.
Low latency is only one piece of the puzzle. Delivering consistent, reliable performance matters just as much for real-world adoption.
Complex voice AI agents need code, not flowcharts. Opinionated platforms that abstract your agent’s backend logic lead to a lack of control at critical moments.
Observing and evaluating voice agents is hard because they are non-deterministic. These challenges scale non-linearly with real usage.
Most teams don’t want to build, maintain and manage their own voice infrastructure.
We're making choices about how we build @Layercode accordingly, and want to hear from more builders in the voice AI space.
If you're building in voice AI: If you could wave a magic wand, what would you change about building voice AI today?
Replies