Teaching 50K+ engineers platform engineering and AI operations reveals clear patterns: how to start with AI ops, where automation helps vs hurts, and what safeguards prevent disasters. Teams that succeed follow similar approaches, while failures cluster around predictable anti-patterns.
This session demonstrates a reference architecture leveraging breakthrough CNCF innovations from 2025: Kagent for Kubernetes-native AI agents, OpenCost for GPU cost tracking, and the observability stack (OpenTelemetry, Prometheus, Jaeger, Fluentd).
Watch as we build an AI agent ecosystem showing how observability agents correlate signals, cost agents prevent overruns, and remediation agents fix issues—all while maintaining human oversight through OPA/Kyverno policy enforcement. This isn't hype—it's honest assessment of what works in early production (troubleshooting, cost optimization) versus what's still maturing (autonomous operations). Leave with practical patterns from thousands of real deployments.