Recursive AI & Compounding Errors

Welcome to Dots In Line, an interactive podcast powered by NotebookLM as a companion to Jamal Khan’s article on recursive AI. In this episode, we explore what actually happens when AI models build subsequent versions of themselves—and why the true challenge isn't a dramatic sci-fi machine takeover, but a quiet, compounding breakdown in logic. Drawing on Khan’s work at the Helix Center for Applied AI & Robotics, we examine the hidden limits of traditional observability tools and see how probabilistic errors quietly cascade through automated steps without triggering a single alert. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit dotsinline.substack.com