Ship Happens: Guardrails for AI-Written Code

AI coding agents are increasing the volume of code teams can produce. How do we turn that speed into reliable releases without making developers the bottleneck for every approval and rollback? This session explores a software delivery workflow where humans define release policies and agents handle repeatable work. We’ll look at why production is a critical validation gate, and how feature flags, progressive rollouts and change-level metrics help teams control the impact of each release. Through a demo and a walkthrough of the Release Autopilot approach, we’ll explore how agents could classify changes, add feature flags, define success metrics, run guarded releases and clean up flags afterward. We’ll also look at how runtime guardrails can detect regressions and disable a flagged change without a redeploy. You’ll leave with a practical framework for deciding what to automate, what to measure and where human judgment belongs as AI becomes part of your delivery pipeline.