Okay, let me tweak my assertion a bit. I agree that evaluating is easier than creating - that is the basis of my assertion too. And I agree that in general sense, you don't need to write to tell if what you're reading is any good, for the purpose of making you informed or entertaining you.

However, when you're using ChatGPT to write things for you, you are in a different position. First of all, you're not the audience - you're the editor. This will make your determinations different, as you're re-evaluating a work you're iterating on, and core points of which you're already familiar with. The same applies to writing on your own (where you're both the writer and the editor for yourself), but writing forces you to focus much more on the text and thoughts behind it, which I believe teaches you to make more nuanced determinations, with much greater fidelity.

Secondly, when you're writing - especially if you bother to enlist the help of an LLM - you usually have a specific goal in mind. Writing a love letter, or an advert, or a business e-mail, or a formal request, etc. requires you to think not just in terms of how it "feels" to you in generic sense of entertainment or knowledge transfer value. You need to put some actual thought into the tone, structure and the wording. Writing, again, forces you to do that.

I can get away with letting GPT-4 write half the text in my correspondence at work (INB4 yes, I have temporary access to company-approved model instance on Azure), because I've written such text myself so many times that I know exactly whether or not GPT-4 is doing a good job (I usually end up having it to do two or three variants, and then manually mix sentences or phrases from each). Even with that experience, I still consider it to be a tool for overcoming mental blocks associated with context switching - I wouldn't dare just having it both generate and send e-mails for me. People who never got the experience of writing specialized correspondence, I just don't think they'd be able to tell if the output of an LLM is actually suitable for the goal one wants to achieve.

Evaluating existing work is often MUCH harder than creation. It often 'feels' easier because most people do a terrible job and offer little more than their opinions. Some intuition: have you ever eaten something you really disliked but you were able to tell that its actually very good because you understood that not all tastes match yours and you can evaluate the various techniques and elements that went into creating the dish? Perhaps more relatable intuition: finding bugs and flaws in a large code base is much hard than writing the code to start with.