ACID assumes human intent behind every commit. AI agents expose this as an architectural gap – and the enterprise transaction model has no mechanism to detect it.
Transactions Assume Intent. Agents Don’t Guarantee It
Tag: performance
Database performance under AI workloads is fundamentally different from human-paced transactional load. AI agents compress think time, expand query fan-out and introduce feedback loops that traditional capacity models were never designed to handle.
Cloud infrastructure adds a further layer of tension: uniform, elastic compute interacts with non-uniform, deterministic database behaviour in ways that become more visible as AI tightens the coupling between them.
AI Agents Don’t Just Add Load. They Change Its Shape
AI agents don’t just add database load – they change its shape. This article explains the three new patterns: compression, expansion and recursion.
AI Can Replace Interfaces, Not Systems of Record
AI can replace interfaces but not systems of record. The database commit is where intent becomes enterprise reality – and that boundary matters more than ever.
The Hidden Cost of Letting AI Agents Query Live Systems
AI agents querying live databases generate unplanned load that breaks enterprise performance assumptions. This article explains the hidden cost for systems of record.
The Cloud Is Built on Uniformity. Databases Are Not
Cloud infrastructure assumes workloads are uniform. Enterprise databases are the exception – and AI is making that tension more visible than ever.
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.
Databases Now Live In The Cloud
Gartner predicted 75% of databases in the cloud by 2022. The industry debate focused on migration – but not on the question that mattered most: what happens to performance?
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