On a tangent, I was a bit confused by the everyday examples given in this article.

"We're often faced with similar trade-offs. You want a meal that's both cheap and delicious? A job that's both well-paid, easy, and fulfilling?"

I really don't feel like "easy" is a dimension I wish to optimize for in a job. It almost feels opposite to what I've actually optimized for - since for me a fulfilling job usually means full of deep technical challenges. I want a job without unnecessary friction, without interpersonal drama, even one that's low stress. But definitely not easy.

  > I want a job without unnecessary friction, without interpersonal drama, even one that's low stress.

Doesn't matter if the actual job is filling glasses of water or building rockets; as long as I can focus on it for 100% of my working hours, I'd see it as an "easy" job.

I get what you’re saying, but I wouldn’t say easy is the opposite of challenging. As a quick example, I would surely find a day job of manual labor harder and significantly less enjoyable than a day job of software engineering challenges.

(And please note that I do not mean to imply that there are no challenges in manual labor or that software engineering is more important.)

Maybe instead of "easy" what they really meant that axis to convey is something more like "low stress" or "not frustrating"

It sounds like you're saying "easy" and "fulfilling" cannot coexist, and obviously they are in tension, but a Pareto frontier still exists there.

Well then, you would prioritize "fulfilling" in your utility function. Others might make a different choice; e.g. a single parent who needs to save time and energy for family might prefer "easy" at the cost of boring drudgery

They’re just hypothetical examples, not meant to apply to everyone.

Felt like covert advertisements.

what you choose for the dimensions is arbitrary, they only chosen thusly to prove the point.

I don't think I've ever seen an example of pareto that wasn't pseudo scientific drivel.