Agentic Data Serving: Reimagining Data Infrastructure for AI

As enterprises deploy AI and LLM features, traditional ETL pipelines have become a critical bottleneck—with data teams spending up to 80% of their time maintaining brittle code instead of driving insights. Agentic data serving, powered by open standards like the Model Context Protocol and schema-agnostic tools like DuckDB, enables AI agents to autonomously discover and query data while tolerating schema changes. This architectural shift could transform data engineering by dramatically reducing technical debt and accelerating the development of AI-powered applications.