by Rhea Purohit
in Learning Curve

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Along with the future of artificial intelligence, I write about mid-century American bank robbers. 

I write scripts for a history podcast, and one would think that it’s the perfect task to outsource to LLMs. I’ve written many of these before, know exactly what’s expected, and am fairly confident I can articulate them in a prompt. I also have existing research so I can give the LLM reliable knowledge to draw from.  

But when my partner asked me if I’m going to use AI to write them, my instinctive answer was: “No, I want to do a good job.” 

After some introspection, I realized that my reaction had nothing to do with AI’s capabilities. I was holding on to a quiet assumption: If AI makes writing easier, something important must be getting lost along the way. Reduced effort must mean reduced quality. Because of this irrational thought, I don’t use AI as much as I can—even though it would free me to focus on the aspects of writing I like more. 

This relationship between effort and perceived value isn’t novel. It’s a human tendency that surfaces in surprising contexts: The American cake mix industry, of all things, grappled with a similar situation decades ago. When cake mix sales fell because their powdered product alienated consumers from the baking process, the industry found an elegant solution: Don’t reduce effort—redirect it. 

As I dug into the psychology behind our relationship with effort, I saw a parallel in our attitudes to using AI for work. I believe the horizon of effort—the energy and attention we invest in our work—isn’t reducing, it’s shifting. This essay explores how I think we can thoughtfully redefine where we entrust our effort…

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  • The cake mix industry learned that consumers don’t always want things to be easier
  • AI is redirecting human effort toward more strategic and creative endeavors
  • The future of knowledge work lies in finding unique ways to differentiate ourselves

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