How we think about data engineering agents, structured context, and turning workflows into reliable execution.
Start here. The problem, the product, and the thesis behind it.
The shift from assistive AI to autonomous data workflows.
How Datus works under the hood — agent design, storage, ETL, and pipeline automation.
Semantic models, structured context, and what makes agents reliable.
MCP, extensions, and how agents connect to real data systems.
Real use cases and how agentic data teams operate.