Move beyond monolith prompts to scale complexity with specialized agents

🎥 Live Webinar 📅 Wednesday, December 17th 🕙 10 AM PT | 1 PM ET

Speakers Theresa Foy — Senior Product Manager, Deepgram Jake Lasky — Senior Applied Engineer, Deepgram

If you’re building complex real-time voice agents, you know the challenge: forcing a single LLM to handle every possible user intent often leads to hallucinations, latency, and rigid conversational flows. Traditional single-agent architectures struggle to maintain context when a conversation spans multiple distinct domains — for example, switching from technical support to billing.

Join this live, technical session to get a detailed breakdown of Deepgram’s Multi-Agent Framework, a pattern designed to solve the “do-it-all” problem. Instead of relying on one massive system prompt, this approach uses an upstream orchestration layer to intelligently route users to specialized downstream agents — ensuring the right context and the right logic at every turn.

You’ll walk away with a blueprint for architecting agent-to-agent handoffs, preserving state across transitions, and implementing the pattern using the Deepgram Voice Agent API.

Learn how splitting logic into specialized sub-agents reduces latency and increases accuracy compared to monolithic LLM prompts.

See how to manage context passing and routing logic between agents — seamlessly and efficiently.

Explore the orchestration logic behind the multi-agent pattern and how to configure downstream agents for specific tasks without hard-coding complex flows.

Discover strategies for defining clear agent boundaries to prevent loops and ensure smooth topic transitions.

Reserve your seat to see how Deepgram’s Multi-Agent framework is redefining the architecture of real-time conversational AI.