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Product point of view
This is where we write through the ideas behind Datus, from category framing to workflow design.
Datus Blog
How we think about data engineering agents, structured context, and turning workflows into reliable execution.
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Start here
If this is your first time here, start with the pieces that explain the Datus point of view.
- From Human-First Data Systems to the Agentic Data Stack
- What Is a Data Engineering Agent? A Practical Guide with Datus
- Agentic Data Engineering vs Traditional Data Engineering
Editor’s picks
- Why AI Agents Need Semantic Context to Work Reliably
- How MCP Changes Data Workflow Automation
- AI Data Pipeline Automation: Use Cases, Architecture, and Tradeoffs
- Why Reliable Data Agents Need More Than Good Prompts
What you’ll find here
This blog lives somewhere between product, architecture, and workflow design.
We write about:
- data engineering agents
- workflow automation and orchestration
- MCP and tool-connected runtimes
- metrics, semantic models, and structured context
- what it takes to make AI useful in production data systems