A data scientist runs a query against a warehouse. The engine finishes the scan in three seconds.
Budgeting for agentic analytics when every question costs something different: token economics, query economics, instrumentation, and the cost controls.
The five layers of an agentic lakehouse and where the MCP server sits: storage, catalog, semantic layer, MCP gateway, and agent surface, plus identity.
Autonomous table optimization when query workloads stop being predictable: observing file layout and query patterns, scoring compaction work, adaptive.
