As AI agents move from prototypes to real production systems, memory becomes the defining challenge. Stateless prompts are not enough. Agents must retain context across sessions, remember user preferences, and retrieve relevant information reliably at scale. Without a structured memory layer, systems quickly become inconsistent, expensive, and difficult to operate.

This session introduces the Redis Agent Memory Server, an open source, production ready solution built to give AI agents durable, structured memory. We will explore the real challenges teams face when adding memory to agentic applications, including what to store, how to retrieve it efficiently, and how to manage memory as systems evolve.

You will learn how to use Redis Agent Memory Server to extract, store, retrieve, and manage the full lifecycle of agent memory. By the end of this session, you will understand how to move from stateless experiments to stateful, scalable, and reliable AI agents running in production.