Artificial intelligence does not need to copy the human brain to advance, yet cognitive science still offers useful guidance. As agentic applications grow, understanding how humans store and retrieve information can help us design agents that act with greater context and reliability.

This talk connects human memory to the practical challenges of building AI agents with memory. We will review the main types of memory in the brain, revisit a landmark case in neuroscience, and relate these ideas to how large language models process information. We will also look at the real difficulties of taking agents to production, where choosing what to store and how to retrieve it becomes the core challenge.

Participants will learn:
- How insights from cognitive science can guide agent design
- The key forms of human memory and their relevance to AI
- What neuroscience reveals about the limits of large language models
- The main obstacles of deploying agents with memory in real systems
- How our work at Redis led to an open-source, production-ready agent memory server
- Practical ways to improve memory in AI agents

This session offers both conceptual clarity and concrete tools for building more capable agentic systems.

Presented at AI Lowlands and confirmed for Devnexus