In this thought-provoking episode, we dive into the evolving philosophy behind building agentic AI—moving away from rigid scaffolding and handcrafted logic, and toward systems that learn, adapt, and scale on their own. Inspired by Richard Sutton’s Bitter Lesson, we explore why the most powerful AI systems rely less on human-designed shortcuts and more on general-purpose learning and computation. We discuss how this mindset shift impacts the design of AI agents, the trade-offs between control and autonomy, and what enterprises need to consider when scaling automation in real-world environments. If you're building or deploying AI at scale, this episode offers deep insight into the why behind the how.