Agentic AI is evolving from hype to hands-on reality—no longer just copilots, but autonomous actors in Kubernetes clusters. But how effective are these AI agents in real-world ops?

This panel brings together builders and operators who've deployed LLM-powered agents at scale in production to share what worked, what broke, and what surprised them. Expect a candid, high-signal conversation on the true strengths and sharp limitations of AI agents for Kubernetes.

SREs, platform engineers/operators—come with questions, leave with a clearer sense of where AI can reduce toil, when it still needs babysitting(human-in-the-loop), and how to experiment and deploy safely.

We’ll cover:

- High-efficacy use cases: RCA, triage, incident summarization
- Common failure patterns: hallucinations, context loss, unpredictability, alert attention
- Evaluation strategies in dynamic prod environments
- Design trends: agent chaining, feedback loops, safety guardrails