The industry is currently racing to integrate AI agents into systems originally designed for human intervention, where reliability still hinges on "human glue"—tribal knowledge, outdated runbooks, and fragmented dashboards. This session posits that achieving trustworthy production autonomy requires a fundamental shift: a new operating layer for SRE. We will explore the concept of an Agentic OS grounded in four essential bodies of truth: code, infrastructure state, runtime signals, and operational knowledge. By moving beyond disconnected artifacts like Git repos, Terraform plans, and traces, we can create a live context graph that agents can query, update, and audit in real time.
We will examine how an AI-native operations layer can be embedded directly into the delivery and runtime path. By continuously ingesting data from CI/CD pipelines, infrastructure drift, and SLO violations, this system produces durable decision traces rather than simple one-off automations. Grounded in real-world architectures and failure scenarios, this session focuses on the practical requirements for transitioning from manual scripts and alerts to truly trustworthy, autonomous SRE systems that provide a clear "why" behind every automated action.
John Jamie is part of StackGen, an Autonomous Infrastructure Platform (AIP) company based in the San Francisco Bay Area. He studied at the University of Pennsylvania’s Wharton School and works at the intersection of infrastructure automation and platform engineering.
