Operations | Monitoring | ITSM | DevOps | Cloud

Claude Mythos may be wrapped in hype, but the core signal is real: AI is making vulnerability discovery much faster, which means defenders have less time than ever to patch and enforce secure configurations. The real risk isn’t just smarter models, it’s that security teams will face a flood of new findings while the window between disclosure and exploitation keeps shrinking.

The IT service management (ITSM) industry stands at a real inflection point. For decades, service desks have operated on a fundamentally reactive model — employees face problems, submit tickets and wait for human analysts to diagnose, triage and resolve their issues. Automation improved throughput within that model, but it never challenged the model itself.

The platform has been live for six months. Workflows are running, the virtual agent is fielding requests, and the vendor dashboard shows deflection numbers are going up. Then someone pulls the actual ticket volume report, and it looks almost identical to the one before the rollout. This comes up constantly in enterprise IT, and most teams respond the same way. They tell themselves the platform needs more automations, a wider user base, and another quarter to mature. Months pass.

In early 2026, two back-to-back Linux kernel exploits, Copy Fail (CVE-2026-31431) and Dirty Frag (CVE-2026-43284 & CVE-2026-43500), shattered assumptions about how quickly attackers can weaponize disclosed CVEs. Dirty Frag, a zero-day Linux vulnerability that affected most major distributions, had PoC exploits published within hours of its disclosure. It’s a stark reminder: the timeline between vulnerability disclosure and active exploitation has shrunk from weeks to hours.

Here’s a story that plays out constantly in enterprise IT, and few people talk about afterward. A team runs an evaluation with multiple vendors using a structured scoring process. Then, they make their choice, but six months into deployment, the platform that excelled in every demo is now struggling with the actual environment. The IT leader who signed off is in a room with their CIO, trying to explain why the numbers fail to match the projections.

I’ve been doing this for over thirty years. Sysadmin, ops lead, global teams, and more data centre migrations than I’d like to admit. Site to site, P2V, V2V, cloud, hybrid, all of it. Every migration gets sold as a clean, well-planned transition. None of them are. They go wrong in very predictable ways. Not because moving infrastructure is especially difficult, but because nobody ever has a clear, current view of what’s actually running, what’s changed, and what still matters.