Operations | Monitoring | ITSM | DevOps | Cloud

AI vs. AI: from alert fatigue to agentic cybersecurity

Jul 15, 2026 By Rootly In Rootly
AI is transforming cybersecurity on both sides of the battlefield. Attackers can now launch highly personalized phishing campaigns at scale and build malware capable of making autonomous decisions. At the same time, security teams are using AI agents to investigate alerts, reduce noise, and respond to threats faster. In this episode of Humans of Reliability, we speak with Nir Soudry, Head of R&D at 7AI, about the shift from alert fatigue to agentic cybersecurity.
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nexthink

The AI Factor You're Ignoring: Employee Behavior

Jul 15, 2026 By Shawn Lazarus In Nexthink
One of the most important realizations emerging across enterprise AI governance discussions is that most risky AI behavior is not malicious. Employees are typically trying to work faster. They are trying to summarize documents, accelerate research, draft communications, analyze spreadsheets, or automate repetitive tasks. In many cases, employees may not fully understand how AI providers handle uploaded information, what data policies apply, or where organizational compliance boundaries actually exist.
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Building a Website with AI: What You Should Know First

Building a Website with AI: What You Should Know First

Jul 15, 2026 By OpsMatters In OpsMatters
The age of artificial intelligence is here, and it has already made many types of otherwise time-consuming tasks that much easier. For some, that includes building a website. Building a website from scratch takes some serious time (and talent, of course). While AI can't take all the creativity out of your hands, it can act as a tool to help you achieve the website's end result that much faster. Of course, overreliance is not the answer, though. So, to get it right, here's what you should know before you start building a website alongside AI.
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cloudzero

What is AI cost observability? A guide to tracking LLM and AI spend

Jul 14, 2026 By Keith MacKenzie In CloudZero
AI cost observability is the practice of measuring, attributing, and analyzing AI workload costs at the request, model, and workflow level in real time. It connects cloud infrastructure spend, inference and token costs, and business attribution (cost per feature, team, customer, or product) so engineering, finance, and product teams can see where AI spend goes and whether it creates value.
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Why the U.S. Locked Down Fable and Mythos: AI, National Security, and the Workforce Squeeze

Jul 14, 2026 By Harness In Harness
The U.S. just barred foreign nationals from accessing two advanced AI models — Fable and Mythos — citing national security. Around the same time, the Five Eyes intelligence alliance warned that AI-enabled cyberattacks are "months, not years" away. In Season 5 of ShipTalk, host Adam and co-host Martin dig into whether that warning is already overdue — and what it means for the people actually defending software.
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pulsant

Why colocation is becoming the foundation of sovereign AI

Jul 14, 2026 By Mark Lewis In Pulsant
The last few years have seen AI conversations dominated by the need for investment in hyperscale infrastructure as firms race to build ever larger training models. But as those conversations evolve, the emphasis is shifting to the next phase of AI adoption, focusing on the scaling of use cases and real-world value. In line with this shift, organisations are looking beyond where AI is trained to the specifics of where it is actually used.
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AI is Exposing Observability's Dirty Secret

Jul 14, 2026 By Speedscale In Speedscale
The 3 pillars of observability are breaking. For years, dev teams relied on Logs, Metrics, and Traces to know when something went wrong. But now? AI agents are writing, deploying, and changing code in real-time. When an AI hallucination pushes a bug to production, standard monitoring sees nothing wrong.To survive the AI era, we need a 4th Pillar of Observability. Watch to find out what it is and why the old way of monitoring just became obsolete.
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