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:
This session offers both conceptual clarity and concrete tools for building more capable agentic systems.
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
- 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.
Raphael De Lio
Redis
Raphael De Lio is an AI and Software Engineer at Redis with over eight years of experience spanning multiple industries and countries. He is passionate about distributed systems and specializes in Java, Kotlin, and building scalable, high-performance software with a growing focus on reliable, distributed agentic systems.
What drives him is bridging the gap between software engineering and AI engineering, bringing the hard-won knowledge of building distributed, scalable systems into the world of AI where those foundations are often missing but matter most.
Originally from Brazil, Raphael spent six years in Portugal before making the Netherlands his home, where he also helps organize the Dutch Kotlin User Group. He loves blending code, community, and creativity to help developers build better systems faster, and with a lot more fun along the way.
What drives him is bridging the gap between software engineering and AI engineering, bringing the hard-won knowledge of building distributed, scalable systems into the world of AI where those foundations are often missing but matter most.
Originally from Brazil, Raphael spent six years in Portugal before making the Netherlands his home, where he also helps organize the Dutch Kotlin User Group. He loves blending code, community, and creativity to help developers build better systems faster, and with a lot more fun along the way.
Samuel Agbede
Redis
Software Engineer and Developer Advocate focused on AI agents and memory systems. I explore how context, retrieval and state shape intelligent behaviour in real-world applications.
Previously an Applied Engineer at JPMorgan, now working in the AI and memory space at Redis. I care about systems that are reliable, observable and built to last.
Previously an Applied Engineer at JPMorgan, now working in the AI and memory space at Redis. I care about systems that are reliable, observable and built to last.