Agenda
Technical Deep Dive + Live Q&A
Today, producing 1,000 lines of code is often a sub-minute operation for modern AI coding agents. Reviewing the same amount of code still takes 30-60 minutes, even for experienced engineers. As agentic workflows scale, this growing gap is becoming the real constraint on how fast teams can safely ship software.
In this webinar, we’ll explore what it means to design agentic AI workflows where failure is expected and correctness is probabilistic. When agents confidently generate large, multi-file changes, traditional safeguards like code reviews, staging environments, and manual rollouts no longer scale. The core design challenge shifts from preventing mistakes to containing them, reducing blast radius, and enabling fast recovery when things go wrong.
We’ll walk through practical, battle-tested techniques for managing risk in AI-assisted development, from development-time isolation and sandboxing to production-time controls that decouple deployment from exposure. We’ll introduce FeatureOps as an emerging approach to release management in the age of AI agents, focusing on runtime control, deliberate exposure, and reversibility.
You’ll see how to integrate FeatureOps directly into agentic workflows, allowing AI assistants to reason not just about what code to write, but how and when to expose changes to users. By making reversibility a first-class input to agent planning and execution, teams can move faster with AI without compromising production stability.
This session is designed for engineers and technical leaders building with AI-assisted coding tools who want to ship faster, embrace agentic workflows, and stay in control as software delivery accelerates.
In this webinar, you’ll learn how to:
– Apply proven techniques to reduce blast radius for AI-generated changes
– Design workflows where failure is expected and recovery is fast
– Treat feature exposure as a runtime decision, not a deployment step
– Make reversibility a first-class input to how AI agents plan and ship code
