Introducing Agent Memory on Databricks

Most AI agents start every conversation from zero. Agent memory on Agent Bricks (Beta) gives your agents durable, long-term memory on Lakebase, in your Databricks workspace, so each conversation starts with what the agent learned from the last one. In this video, you'll learn how agent memory works and how to add it to your agent. Agent memory has three pieces: • Managed sessions: record each conversation, turn by turn • Managed memory: keep what's worth knowing about each user, such as preferences, facts, and workflows • Memory pipelines: run in the background to distill sessions into memory