The recent advances in reasoning-capable Large Language Models (LLMs) have yielded impressive benchmark improvements and transformed commercial AI products. These successes have been particularly pronounced when we can establish clear objectives and verification mechanisms, such as in mathematics and programming. But where do reasoning LLMs currently fall short? How will the dynamics of human-AI collaboration evolve? What are the ongoing impacts on learning and education? In this talk, I will endeavor to speak to, at the very least, some of these questions.