Context Is Everything: Lakebase Agent Memory
Build a complete, stateful LangGraph agent and deploy it as a Databricks App. You'll create an assistant that answers business questions by calling Unity Catalog function tools over live data, sustains multi-turn conversations through short-term checkpointed state, and recalls each user across sessions days apart via persistent long-term memory. Along the way you'll see why context is everything: an agent is only as good as the context assembled into its prompt, and memory — backed by Lakebase Postgres — is how that context survives beyond a single inference.
• Databricks workspace navigation.
• Unity Catalog fundamentals.
• Unity Catalog Functions.
• Databricks Apps basics.
• Databricks CLI / SDK basics.
• Lakebase Autoscaling concepts.
• Connecting to Lakebase from Python.
• LangChain and LangGraph basics and tool concept.
• Agent concepts and creation
• MLflow tracing
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