This tutorial explores the intersection of generative AI and reinforcement learning, demonstrating how generative models can be understood as RL agents and environments, and conversely, how RL can be viewed as generative modeling. It aims to bridge the gap between these fields, showing how insights from each can enhance the other. The workshop will cover topics such as reinterpreting generative AI training through an RL lens, adapting generative AI to build new RL algorithms, and understanding how AI agents interacting with tools and humans create a new generative model. It will also discuss future directions and open problems, focusing on how RL can shape the future of foundation model training and enable generative AI systems to construct their own knowledge.