Nir Zicherman argues that effective learning requires more than just access to information—it demands structure, multimodal engagement, and sustained guidance. Unlike general-purpose LLMs like ChatGPT, dedicated platforms like Oboe are designed with pedagogy in mind, maintaining focus on user goals while enabling exploration. Learning is less about constant activity and more about receiving well-timed, diverse content—videos, readings, quizzes—that reinforces understanding. AI agents today can initiate learning but struggle to maintain engagement over time, lacking re-engagement tools and continuity. Oboe addresses this by generating personalized, goal-oriented courses that evolve with the learner, such as one on quantum physics that blends historical experiments with conceptual clarity. The discussion also touches on how embedding spaces in AI mirror the non-intuitive nature of quantum mechanics, revealing deeper parallels between machine and human cognition. Ultimately, the challenge isn’t accessing knowledge—it’s designing systems that help people stay motivated, process complexity, and truly learn.