Agentic Data Engineering vs AgentPulse, drift investigation for multi

Agentic data engineering uses AI agents to build and maintain data pipelines from plain-English intent. How it works, the tools, and how to trust it.

Open-source drift investigation for multi-agent systems: which agent drifted, where it originated, and what to check next.

About Agentic Data Engineering

Agentic data engineering uses AI agents to build and maintain data pipelines from plain-English intent. How it works, the tools, and how to trust it. It's the harness around it: the grounding that tells the agent which answer is right, and the controls that catch a wrong one before it ships. A governed semantic layer lifts text-to-SQL accuracy from about 51% to over 90%, proof that context, not capability, decides whether an agent's SQL is correct.

About AgentPulse, drift investigation for multi

Open-source drift investigation for multi-agent systems: which agent drifted, where it originated, and what to check next. What did change is the payload it receives from writer, starting at the same run. So critic is probably downstream damage, not the source. After the change, writer responses run ~180% longer and drop the section structure critic expects, earlier payloads were structured summaries, newer ones read as prose. If restoring the format fixes critic, make the fix in writer.