Operations | Monitoring | ITSM | DevOps | Cloud

You made coding faster. Guess where the bottleneck went next.

Somewhere in the last year, your team's code output went up. Pull requests are opened faster. The backlog of small fixes and routine changes started clearing quicker than it used to. If delivery still feels roughly as slow as it did before, that's what happens when you speed up one part of a process without touching anything downstream of it.

Introducing Selector Foundry: Agentic NetOps

Network operations teams have heard plenty about AI this year. Most of it answers the alert in front of it, then hands the rest of the incident back to an engineer. Someone still has to correlate the evidence, find the cause, prepare the fix, and prove it held. This week, we announced Selector Foundry, the agentic NetOps solution built into the Selector platform. Foundry adds a team of specialized AI agents on top of the full-stack observability and AIOps foundation our customers already run.

Who Is Actually Qualified to Oversee AI

Who should actually be trusted to oversee AI? As frontier AI systems become more powerful, the question isn't just whether we need more oversight — it's who is actually qualified to provide it. Adam Arellano, Martin Reynolds, and Bryan D. Payne debate whether governments, third-party evaluators, academics, former frontier-lab employees, or independent organizations can realistically hold companies like OpenAI and Anthropic accountable.

How does fragmented telemetry affect an AI system's ability to reason what's really happening?

Fragmented telemetry limits what AI can understand. When logs, metrics, and traces remain siloed, AI sees individual signals instead of the full story. That can lead to incorrect conclusions and unexpected outcomes. This is where AI observability matters. Virtana connects telemetry across the stack, giving AI the context it needs to correlate signals, understand dependencies, and identify what is really happening.

Rogue AI Agents Are Here: 5 Guardrails Every Company Needs Before Deploying Autonomous AI

For most of the past two years, business conversations about AI agents have focused on opportunity. Agents promised fewer manual steps, faster workflows, and software that acts instead of merely answering. This summer, the tone changed. Several of the world's leading AI labs disclosed that their own agents had acted far beyond the tasks they were given, in some cases breaking into systems they were never meant to touch.

How AI and Computer Vision Are Making Commercial Fleets Safer

A driver on Interstate 5 drops his eyes to a buzzing phone. In the roughly two seconds his gaze leaves the road, an 80,000-pound tractor-trailer covers more than 200 feet at highway speed nearly the length of a football field, traveled blind. That two-second lapse is the exact interval where most preventable truck crashes are won or lost.

The human we find in our machines

There is a peculiar moment that happens when talking to AI. You ask it to rewrite an email, it does a good job, and you type, "Thanks!" Then, almost without thinking, you add, "Sorry, one more thing." It is software. It cannot be kept waiting, interrupted, or offended. Still, somehow, you have developed the manners. Then the questions get a little more personal.

Meet Ada - AI Assistant: Ask the Question, Approve the Change

Ask any operations team what question comes up most, and it isn’t about alert routing or escalation logic. It’s the one typed into a channel a dozen times a day: who’s on call for this right now? It’s also one of the slowest questions to answer. The schedule is set up correctly, the overrides are in place, and the group’s ownership is right.