---
title: "From Stateless to Stateful: Orchestrating Real-Time Voice & Messaging Agents with Twilio and Amazon Bedrock"
category: "talks"
date: "2026-06-30"
time: "12:05pm-12:25pm"
track: "Expo Stage 2 NW"
room: "Expo Stage 2 NW"
speakers: ["Rishab Kumar"]
sourceLabels: ["Official conference schedule", "Public YouTube metadata"]
scheduleTrack: ""
scheduleRoom: "Expo Stage 2 NW"
scheduleLabels: ["Expo Stage 2 NW", "session", "confirmed"]
---
# From Stateless to Stateful: Orchestrating Real-Time Voice & Messaging Agents with Twilio and Amazon Bedrock

## Conference Context
- Date/time: 2026-06-30 · 12:05pm-12:25pm
- Track/room: track TBD · Expo Stage 2 NW
- Speaker(s): Rishab Kumar
- Session type/status: session · confirmed

- Track: track TBD
- Room: Expo Stage 2 NW
- Session type: session
- Status: confirmed

## Session Description
We have all had that maddening customer service experience: you text a support line about a delayed flight, receive a confirmation, but when you call in a minute later, the voice agent asks, "How can I help you today?" completely blind to the SMS you just sent. This is the "Channel Amnesia" problem. While businesses are pouring billions into generative AI, most agents are still built on stateless architectures that forget customer context the second a session ends. In this session, we will cure AI amnesia. You will learn how to orchestrate stateful, production-grade AI agents across SMS and Voice using Twilio Agent Connect and Amazon Bedrock. We will dive into why traditional serverless compute fails stateful agents, how to leverage AWS Fargate for isolated, long-lived sessions, and how to configure Bedrock AgentCore over WebSockets to hit sub-50ms streaming voice latency. No slide-ware here expect a live, cross-channel demo and open-source code you can deploy tomorrow.

## Media Evidence
No related AI Engineer channel video found yet.

## Evidence Graph
This evidence graph is generated from currently linked source material: official schedule text, related video pages, cached transcripts, visible slide text, dense/reconstructed slide pages, and AI slide-classification audits.

### Media Signals
No linked video, transcript, or slide source has been attached yet.

### Agent Reading Notes
Use these signals to refine the synopsis, topic links, people/company context, and method notes. If a source is a related external video rather than an exact official recording, keep it framed as supporting evidence.

## Transcript Status
No official session recording transcript was found by exact title match on the AI Engineer YouTube channel during this run.

## People
- [[rishab-kumar]]

## Notes
- Pending transcript synthesis when an official recording or confirmed matching video is available.

## Synthesis
### Synthesized Breakdown
# From Stateless to Stateful: Orchestrating Real-Time Voice & Messaging Agents with Twilio and Amazon Bedrock ## Conference Context - Date/time: 2026-06-30 · 12:05pm-12:25pm - Track/room: track TBD · Expo Stage 2 NW - Speaker(s): Rishab Kumar - Session type/status: session · confirmed - Track: track TBD - Room: Expo Stage 2 NW - Session type: session - Status: confirmed ## Session Description We have all had that maddening customer service experience: you text a support line about a delayed flight, receive a confirmation, but when you call in a minute later, the voice agent asks, "How can I help you today?" completely blind to the SMS you just sent. This is the "Channel Amnesia" problem. While businesses are pouring billions into generative AI, most agents are still built on stateless architectures that forget customer context the second a session ends. In this session, we will cure AI amnesia.

### Speaker And Company Context
- [[rishab-kumar|Rishab Kumar]] — Staff Developer Evangelist at [[twilio|Twilio]].

### Topics Covered
- [[coding-agents]]

### Derived Links And Source Material

### Novel Concepts / Clever Methods
- No highlighted novel concept has been detected yet.

### Evidence Boundary
This synthesis is based on the official schedule and linked source pages. It should be revisited when exact session recordings or transcript-backed secondary sources are available.