What if artificial intelligence doesn’t get smarter because we design it better but because we deploy it?

In this episode, we explore a recent research insight showing that AI systems can improve their planning abilities simply by being released into the real world and learning from what works. No explicit rewards. No hand-crafted training loops. Just repetition, validation, and survival.

Using the lens of nation-building and country-level development, we draw a powerful parallel: societies don’t evolve through perfect plans, but through countless small corrections, policies that work get repeated, failures quietly disappear, and systems slowly adapt.

This episode connects cutting-edge AI research with a deeply human idea:
maybe the future of intelligence isn’t about building minds smarter than ours but understanding how intelligence emerges from experience, feedback, and shared reality.

Perfect for founders, technologists, policymakers, and anyone curious about how AI, systems, and societies truly learn.