Operations | Monitoring | ITSM | DevOps | Cloud

Here's why AI companies don't want you to know how much AI actually costs.

Recorded at @DevOpsLive Most teams have “done DevOps” and “built a platform,” but still wrestle with the same core problems: platforms that developers dodge, AI that accelerates coding while quietly degrading delivery performance, security and compliance that can’t keep up, cloud bills that keep climbing, and incident response that hasn’t caught up with cloud‑native complexity.

AI can generate a UI in seconds. So what do designers actually bring to the table? Marcela, Principal Product Designer at Rootly and former Founding Designer at Ramp, has spent 20 years in design. Her answer: taste isn't about aesthetics or crafting pleasant interactions. It's about asking the uncomfortable questions, and choosing the right problem, not the easiest one.

Building AI applications? There's a lot more to monitor beyond errors. With tracing enabled, Sentry's built-in AI Dashboards give you deep visibility into how your agents are actually performing. This video walks through three key dashboard views: You'll also see how to drill from a dashboard widget straight into the trace explorer to pinpoint the root cause of errors, how to duplicate and customize dashboards to fit your needs, and how to set up monitors with alert thresholds - like getting notified if your LLM calls exceed 20 seconds.

AI agents write the code. CircleCI makes sure it actually ships. The CircleCI plugin for Codex is live.

AI coding tools help you ship features faster than ever, but test coverage often can't keep up. In this video, we show you how CircleCI's Chunk autonomous CI/CD agent finds untested code in your codebase, writes tests to cover it, and opens a pull request for your review. What you'll learn: Chunk works directly inside your CI/CD pipeline, giving it access to your build history, test results, and coverage reports. That means smarter tests, not just more tests.