For years, reliability engineering has focused on runtime operations: monitoring systems, responding to alerts, and reducing mean time to recovery (MTTR). But as distributed systems grow more complex, diagnosing failures in production becomes increasingly difficult. A new model is emerging: the Reliability Development Lifecycle (RDLC). In this paradigm, reliability is evaluated continuously during software development. AI-powered systems analyze infrastructure changes, service dependencies, deployment plans, and historical incident data to identify reliability risks before code ever reaches production. This shift moves reliability from an operational concern to a first-class property of software development. In this keynote, we explore how AI-driven Site Reliability Agents can embed reliability intelligence directly into CI/CD pipelines, developer workflows, and infrastructure planning—preventing incidents instead of merely responding to them. The goal is no longer just faster incident response.
Bennett Gould is a Site Reliability Engineer, Software Engineer, and Solutions Engineer at NeuBird AI based in the San Francisco Bay Area. He focuses on reliability engineering and modern infrastructure, working at the intersection of software development and production operations. Bennett is also the organizer of the SF Reliability Engineering Group, a community that brings practitioners together to share knowledge and advance reliability practices.
