Cloud infrastructure assumes workloads are uniform. Enterprise databases are the exception – and AI is making that tension more visible than ever.
The Cloud Is Built on Uniformity. Databases Are Not
Category: AI
AI has rapidly become the dominant narrative in enterprise technology. But most discussions focus on models, tooling, and interfaces – not the systems those models depend on.
In practice, AI is only as effective as the data it can access, the latency it can tolerate, and the systems it can safely interact with.
Why We Spent 20 Years Protecting Databases from Analytics (and Why AI Just Broke That Truce)
For two decades, DBAs protected production databases from analytics workloads. AI agents have ended that truce and the consequences go deeper than most realise.
AI Doesn’t Read Dashboards… and That Changes Everything for Databases
AI agents bypass dashboards and query databases directly. This article explains what that means for the architecture of enterprise data systems and systems of record.
Databases Were Built for Humans – AI Agents Change the Equation
Databases were designed for human-paced interaction – sessions, think time and deliberate intent. AI agents remove all three assumptions simultaneously.
Inferencing Is a Database Problem Disguised as an AI Problem
AI inferencing is a database problem disguised as an AI problem. Real-time model workloads expose latency and concurrency demands that enterprise storage wasn’t designed for.
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