The primary challenge in building agentic systems is deciding what to remember, where to store it, and how to retrieve it when it matters most. This workshop provides a practical framework for architecting memory systems that actually work in production. We explore the critical storage patterns and retrieval strategies necessary to keep your agentic systems performant and contextually aware.
Key Takeaways:
- Identify different types of memory required for agentic systems
- Explore storage patterns for persisting memories and structuring them for retrieval
- Practice retrieval strategies combining Vector Search with metadata, recency and other signals
- Learn to manage the memory lifecycle to create, update, or prune memories efficiently
Building memory is the final step in creating truly autonomous agents. View this session on-demand to gain a structural understanding of memory architecture and ensure your AI applications are built for long-term reliability and performance.
After you’ve watched the session, be sure to take our Memory for AI Applications skills check and earn a skill badge.
