The debate surrounding AI's impact on work is less about reduction and more about the relocation of intellectual tasks. Criticisms of AI-generated content often mistake the means of production for intellectual merit, assuming manual effort inherently equates to higher value. Reading and writing themselves are interfaces, technologies that structure thought and communication. Similar to other interfaces, the "friction" in reading and writing can be either purposeful or incidental. Incidental friction, like basic spelling, might be developmental for a novice but is a distraction for an expert. Technologies, including AI, have historically reduced incidental friction in written language. Generative AI differs by engaging more directly with the cognitive aspects of tasks like synthesis and interpretation. The intellectual work with AI shifts from production to judgment and verification. AI necessitates decisions about delegation, trust, and the accuracy of generated content. In education, AI can remove incidental friction for learners who have mastered a skill but diminish learning for those still developing it. AI weakens the traditional link between polished prose and clear reasoning, making it harder to assess genuine understanding. Rethinking assessment is crucial as AI can produce convincing output without deep comprehension. The focus should be on how AI is used—whether it assists expression or performs the core thinking. AI has not created problems like bad prose or fabricated citations but can exacerbate them and make them harder to detect. Overly fixating on AI's negative uses risks hindering the exploration of its potential for productivity and intellectual amplification. Preserving old practices simply due to familiarity rather than critically evaluating their purpose is unproductive. The true question is not whether AI makes things easier but what capacities we value and how AI affects their development.