Context Engineering for Data Agents
September 10, 2026Why text-to-SQL accuracy collapses on enterprise schemas, the five kinds of context an agent needs, where each one hides, and how to make the semantics legible.
Why text-to-SQL accuracy collapses on enterprise schemas, the five kinds of context an agent needs, where each one hides, and how to make the semantics legible.
Managing the total cost of agentic analytics: token budgets, query throttles, unit economics, and the FinOps discipline that keeps AI spend under control.
Cross-posted. This article’s canonical home is Alex Merced’s Lakehouse Blog. The Buyer’s Scorecard for Agentic Analytics: Evaluating Tooling…
AI agents need more than metric names. They need composable business logic that survives multi-step analysis.
Agentic AI announcements are useful when they validate the need for governed data, semantic context, and cost-aware execution.