As AI systems grow more capable, their usefulness hinges not just on what they know, but what context they understand. In this talk, Ruchir Jha, CEO of Cardinal — an AI-powered observability company, unpacks the emerging discipline of context engineering: the art and science of feeding AI the right information, at the right time, to make sense of complex, high-dimensional infrastructure systems.

Drawing on real-world use cases from cloud-native observability, the talk explores how AI can go beyond dashboards and alerts to reason, adapt, and troubleshoot like an SRE. We’ll explore lessons from building systems that turn noisy telemetry into structured insight, and how context-aware AI is redefining reliability, performance, and cost-efficiency in modern infrastructure.

Whether you're working on AI models, backend systems, or distributed ops, this talk will give you a new lens on how to make machines think contextually and why that's the next frontier in AI for infrastructure.

I am the CEO & Co-Founder of Cardinal, an AI-native observability platform built for modern infrastructure. Before this, I spent seven years at Netflix leading observability engineering including building petabyte-scale systems used daily by thousands of engineers. At Cardinal, I’m focused on pioneering context-aware observability, so ops teams can move beyond dashboards and alerts, and toward intelligent systems that think and reason. I have spoken at SREday San Francisco before, on topics like cost-neutral cardinality in observability, and appeared on podcasts discussing how AI can reduce spiraling observability costs through strategic instrumentation and tooling choices.