Operations | Monitoring | ITSM | DevOps | Cloud

AI agents are moving fast. For enterprises, the bigger question is how to make them useful, trusted, and safe enough to take action. In this episode of Agents of IT, Zach Austin and Ian Coppock unpack what it takes to move from experimenting with AI to operationalizing agentic AI across the enterprise. They explore why organizations are racing to deploy AI before defining the problems they want to solve, why governance and scoped responsibilities are critical, and why the real value of AI comes from fixing and orchestrating the workflows underneath it.

Join Terry Chevalier, Founder and Managing Director, Sunstone Associates to explore why rural markets are emerging as AI hotspots, what Neocloud developers need, and how broadband providers can capitalize on this growing opportunity.

Six engineers, two QA, a product owner and a Scrum Master used to be a normal squad. With today's tooling, that's bloat. Teams are being rebuilt around three people. Not because the work got smaller — because agentic tooling absorbed the parts that needed all those hands. The engineer's job shifts from writing the code to directing the agents that write it, and owning the outcome that comes out the other end.

With SIGNL4, planned and unplanned absences can be managed right from the mobile app.

Learn more: speedscale.com.

The model, the serving layer, and the agent asking questions all sit on local hardware. The first thing it debugs is the AI stack it is running on. No external inference provider in the path.

There’s a new class of cloud provider on the block in AI infrastructure, built specifically for GPU access instead of trying to do everything. We’ve got something in the works for exactly this kind of connectivity too Follow for weekly cloud watching with @digital.byte_ comment “cloud” to connect with our experts.

Learn how to implement end to end observability and monitoring for Grok Build, xAI's terminal coding agent, using OpenTelemetry and SigNoz. In this video, we walk through turning on Grok Build's native OpenTelemetry exporter, collecting metrics and structured session events, and visualizing everything in SigNoz to gain real time visibility into token usage, sessions and turns, tool calls and their outcomes, error categories, and startup latency. Grok Build ships its own exporter, so instrumenting it is a matter of configuration, with no library to install and no collector to run.

Learn how to implement end to end monitoring and observability for GitHub Copilot Chat using OpenTelemetry and SigNoz. In this video, we walk through enabling the OpenTelemetry exporter built into the Copilot Chat extension in VS Code, collecting a trace for every agent turn, and visualizing everything in SigNoz to gain real time visibility into model calls, tool executions, token usage, prompt cache savings, latency, and failures. Copilot Chat ships its own OTLP exporter, so there is no instrumentation library to install and no collector to run.

See how Cribl's AI Observability App gives teams one place to search, investigate, and report on AI telemetry across models, tools, and environments. In this 5-minute demo, we tackle cost, quality, security, and governance blind spots. Start treating AI observability as a telemetry problem. Collect once, use everywhere, no lock-in.