Have you ever felt that AI music tools are powerful, yet frustratingly opaque? You get a stunning piece of music, but you have no idea how the AI created it, making it impossible to truly collaborate or guide the creative process. This "black box" problem has been the biggest barrier to AI becoming a true artistic partner for musicians. In this episode, Ran Chen unpacks how he is breaking open this black box using Agentic AI. We move beyond simple prompts and outputs to a world of AI systems that can reason, explain their choices, and collaborate with artists on a deeper level. This is where AI music gets truly interesting, transparent, and intentional. **In this episode, you'll learn:** * Why is the "black box" problem the single biggest hurdle for AI as a serious artistic collaborator? * What is an Agentic AI, and how is it different from just using a prompt? * How can breaking down a musical task for an AI lead to more transparent and creative results? * Can an AI really explain its own artistic "reasoning"? * What happens when a musician can finally look inside the AI's decision-making process? * Is it possible to "debug" AI-generated music and teach the AI your personal artistic preferences? * How does this level of AI interpretability change the role of the human artist? * Could these new agentic systems help us discover entirely new forms of musical theory? Follow my YouTube: https://www.youtube.com/@chenran818 or listen to my music on Apple Music, Spotify, or other platforms: https://ffm.bio/chenran818