Engineering organizations are hitting a Productivity Paradox. AI tools are generating more code than ever, yet the time it takes to ship that code safely to production in large-scale environments remains stagnant. The bottleneck has shifted from writing code to reviewing, validating, and trusting it. At Roblox, we've moved beyond coding assistants to build an AI-Native Engineering Platform, shifting from human-driven workflows to a fully agentic software development lifecycle.
In this session, we'll break down the architectural requirements for achieving a prompt-to-production development cycle. We'll detail how we replaced manual bottlenecks with a system where autonomous agents handle much of the toil: self-healing codebases, automated API migrations, and agentic guardrails that maintain architectural integrity across twenty years of institutional memory. We'll dive into the technical framework, Exemplar Alignment and hybrid symbolic-vector representations, that allowed us to achieve a 60% PR acceptance rate by teaching AI to reason like our senior domain experts. Crucially, we'll also discuss how to measure what actually matters in the new world of AI-driven engineering.
