The question "How do we use AI?" has shifted from the zeitgeist to a deafening noise where all answers feel equally valid and equally absurd. "It is a tool." "It is a partner." "It is cheating." "It is devaluing work." We are exhausted by the debate because we are focusing on the wrong side of the equation: we are looking at what the technology can do, rather than what we can do with the technology. To the instrumentalist, this is a matter of utility: How do we make it faster? To the cognitivist, this is a question of ontology: What does it do to the thinker?

If I design the argument, does it matter who types the words?

I started with a thesis on Macbeth that I had written in a Faculty meeting exploring how to scaffold student's higher thinking through sophisticated thesis creation. I was curious what could develop if I explored it fully with my AI.

So I put my thesis in and asked the AI to write the essay that the thesis suggested. It could have ended there, it gave me a more than adequate essay.

Had I stopped at that point, I may have gone into a fear spiral about how students would replicate that process and how the human race was doomed.

Luckily, I kept going.

This White Paper presents a compelling alternative to current approaches to AI: the Friction Framework. This is a premium, "slow-tech" methodology that functions as the strategic antidote. We argue that intentionally designed, manageable challenges—"positive friction"—are not impediments but catalysts for deeper learning, enhanced creativity, and more resilient skill development.