Jay Caspian Kang’s musings on generative AI make for an insightful read. Kang first dispenses with concerns about generative AI tools as only being used for cheating, pointing out that rates of cheating remain largely the same as from the pre-LLM world. Probing deeper, Kang sees the arrival of generative AI tools as a provocation, situating these tools in broader conversations about teaching, learning, and curriculum. When viewed as continuous with previous moments of technology-induced worry (like graphing calculators, Wikipedia, or the broader internet-inspired move away from content knowledge), generative AI tools represent not so much a challenge, but rather as an opportunity to rethink what it is we do in school. For example, Kang wonders, “when we think about students’ work, where do we draw the line between what has sprung out of their developing mind and what has not?” This question arises with new urgency in an age of LLMs, but it should be an ever-present reflection for educators. Connecting the agita over generative AI to broader questions of curriculum and skills “gives us a chance to reemphasize the work-habit part of schooling and to walk away from claims that the books that children read are somehow dangerous or that only one version of history can be taught.” In other words, this new technology forces us to think about what we really want students to get out of their classroom and school experiences – and reminds us that the work of learning can never be automated.