The rise of generative AI and Large Language Model-based tools has a significant impact on both the field of computing, and computing education. Computer scientists, educators, and practitioners are having heated discussions about the changes in the nature of programming. A consequence might be that we need to teach programming at different levels of abstraction, with the need for different skills. At the same time, there is an opportunity to use LLMs to support students by generating formative feedback, explanations, and hints for programming tasks. However, LLM-based support can often not be used directly, and it depends very much on the learning goals and context if it is effective. In this talk I will address how generative AI might change learning programming, that we should clearly distinguish between the different circumstances in which people learn to program, and how we can use and evaluate LLMs to support in these different cases.