Master the five-step methodology for designing AI agent workflows that actually work. Learn how to transform sticky-note interactions into productive collaboration.
Data engineering is shifting from writing code to declaring intent. The rise of model-driven data engineers who design semantic models rather than implement pipelines, and what this means for the future of the discipline.
The problem with AI in data engineering is not capability - it is context. Close the gap architecturally with specialized agents and declarative platforms.