Artificial intelligence is progressing from prompt-driven models to agents capable of choosing goals, adapting strategies, and, ultimately, edging toward super-intelligent performance. This trajectory is already altering how learners acquire knowledge and how educators design learning experiences. Using both conceptual analysis and field observations from AI-mediated classrooms such as RVD.AI and Edumaia, this chapter explores what education gains, and risks, when intelligent agents participate actively in teaching and learning. It argues that the educational priority shifts from transmitting technical content to cultivating capacities that current algorithms only approximate: intentional moral agency, causal reasoning situated in real contexts, interdisciplinary synthesis guided by values, and reflective decision-making under uncertainty. As AI-native students arrive with expectations shaped by continuous dialogue with agents, universities are challenged to help them collaborate with, interrogate, and creatively extend these systems rather than compete against them. Re-centering human judgment and ethical responsibility, the chapter outlines principles for integrating AI agents into education while ensuring that human learning remains the ultimate goal.