This article discusses the evolution of data engineering as it adapts to the growing role of AI agents in 2026. It emphasizes the need for reliability, context, and safety within data platforms, highlighting the shift from human-centric workflows to autonomous systems that require new architectural approaches.

The dbt MCP Server is designed to enhance the reliability of AI agents by providing a robust framework for managing and orchestrating machine learning workflows. It offers tools for version control, testing, and deployment, ensuring that AI models are consistently reliable and performant in production environments. By integrating best practices in data management, it supports teams in building and maintaining trustworthy AI systems.