Agents Pushing the Boundaries of Production Data
Famous_Disk_7417 · reddit · 2026-07-18
The author shared their experience testing Databricks' Genie Code in a production data environment: it can plan multi-step tasks within a single thread, such as feature profiling, model training, writing to MLflow, and generating dashboards.
They believe the true value of such tools lies in their ability to restrict visible data based on Unity Catalog constraints and ask for confirmation before modifying tables; in contrast, general-purpose MCP agents are more prone to errors in data lineage and governance.
The author concludes by asking where people draw the boundaries for agents—which operations can be executed directly, and which should only provide diff suggestions first? In production environments, are these guardrails reliable enough?
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