Addressing the challenges of unstructured data governance for AI

Large enterprises in regulated industries, especially in data-rich financial services and insurance, have invested significantly in data governance programs. Other businesses have been catching up as part of their efforts to become more data-driven organizations. Data governance often starts with defining policies, classifying data sources, establishing data catalogs, and communicating non-negotiables.  But look a little…

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The cookbook for safe, powerful agents

As companies move from experimenting with AI agents to deploying them in production, one pattern becomes clear: capability without control is a liability. Agents operate in long-running, stateful environments. They browse the web, read repositories, execute shell commands, call APIs and interact with internal systems. That power is transformative — and it meaningfully expands the…

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Enterprises are rethinking Kubernetes

For years, Kubernetes held an almost mythic place in enterprise IT. It was positioned as the control plane for the future, the standard abstraction for cloud-native systems, and the platform that would finally free enterprises from infrastructure lock-in. To be fair, some of that was true. Kubernetes brought discipline to container orchestration, enabled portable deployment…

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The Modern Data Stack Was Never Built to Make Decisions

I was in a meeting recently with a VP of Data at a mid-size enterprise when she said something that stopped me. We were talking about her team’s quarterly roadmap, and she paused and said, almost to herself: “We have faster pipelines than we’ve ever had, and somehow decisions still take a week.” She wasn’t…

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