Operations | Monitoring | ITSM | DevOps | Cloud

Devs have a habit of solving their own problems before anyone else's and the AI boom is repeating that pattern.

In just two minutes, learn how our AI-powered platform unifies control across Windows, Mac, Linux, Mobile, and even VR/XR headsets. Discover how to eliminate tedious tasks with automated patching, zero-touch onboarding, and self-healing capabilities—allowing your team to focus on strategy instead of firefighting. What you’ll see in this video.

#aiagents #claudecode #podcastclips

Learn what it’s like to work as an engineer at Cribl, a remote-first company building the AI platform for IT and security data. In this recruiting video, Cribl’s engineering and support leaders share how fully distributed teams collaborate, solve hard data problems, and grow their careers while working from around the world. You’ll hear from managers and leaders in site reliability engineering, security incubation, and technical support about.

Your agent writes code fast, but you shouldn't have to see it until it's right. Chunk sidecars are lightweight microVMs that work inside the agent loop, requiring agents to pass pre-push validation in a CI-like environment before they declare they're "done." That means no massive CI pile-ups, no long round-trips that risk resetting your agent's context. You're sending code you already know is good.

Most AI applications in production right now were shipped on vibes. A developer ran a few queries, liked what they saw, and pushed to prod. Laurie Voss argues that's the core reason so many AI products feel broken, and the fix is simpler to name than it is to do: write the tests.

This episode of Ivanti's "IT Insider" series that explores the critical challenges organizations face when moving from AI experimentation to full-scale deployment. The discussion centers on three main themes: The AI Governance Gap: Guests Brooke Johnson and Sterling Parker discuss the "governance gap" where organizations deploy AI faster than they can establish policies. They highlight the risks of Shadow AI (unsupervised AI use) and the importance of having an AI Governance Council to ensure responsible use.

AI agents are powerful. They're also unpredictable, non-deterministic, and capable of doing things you didn't ask them to do, as the Rome Alibaba and Claude Mythos case studies make very clear. The answer isn't to avoid agentic AI. It's to run it properly. In this demo, Ben Norris, founding engineer at relaxAI, shows how to build a fully sandboxed AI agent environment from scratch, an ephemeral Civo VM provisioned via Terraform and GitHub Actions, locked down with egress policies, an unprivileged Linux user, and hard resource caps, running a Claude Code session pointed at the relaxAI API.