Agentic AI exposes what we're doing wrong

"Agentic AI has changed cloud computing, but not in the way the hype machine wants you to believe. It hasn't magically replaced engineering, nor has it made architecture irrelevant. It has made weak architecture, fuzzy governance, and sloppy cost controls impossible to ignore. If you are already running cloud with strong disciplines, agentic AI is an accelerant. If you aren't, it's a stress test you will fail, publicly and expensively."

"Agentic AI is an AI system that can autonomously plan and execute multistep actions toward a goal, often by using tools and services in its environment. That's the key difference from "chat": An agent doesn't just recommend what to do; it can actually do it, repeatedly, at machine speed, and it will keep doing it until you stop it or constrain it properly."

Agentic AI operates as a continuously operating software workforce that can plan, decide, act, and iterate, behaving differently from traditional applications. Autonomous agents can provision resources, call APIs, move data, modify configurations, open tickets, trigger workflows, and chain services. Autonomous decision loops introduce failure modes different from fixed request/response web apps. Weak architecture, fuzzy governance, and sloppy cost controls become impossible to ignore under agentic workloads. Strong cloud disciplines make agentic AI an accelerant; weak disciplines make it a public, expensive stress test. Traditional networking assumptions like perimeter thinking, coarse segmentation, and growing allow lists become actively dangerous.

Read at InfoWorld