I half agree. But two points: 1) if you can formalize your instructions ... then future instances can be fully automated. 2) You are still probably having the AI perform many sub-tasks. AI-skeptics regularly fall into this god-of-the-gaps trap. You aren't wrong that human-augmented AI isn't 100% AI ... but it still is AI-augmentation, and again, that sets the stage for point 1 - to enable later future full automation on long enough timecycles.

There is a lot to be done with good prompting.

Early on, these code agents wouldn't do basic good hygiene things, like check if the code compiled, avoid hallucinating weird modules, writing unit tests. And people would say they sucked ....

But if you just asked them to do those things: "After you write a file lint it and fix issues. After you finish this feature, write unit tests and fix all issues, etc ..."

Well, then they did that, it was great! Later the default prompts of these systems included enough verbiage to do that, you could get lazy again. Plus the models are are being optimized to know to do some of these things, and also avoid some bad code patterns from the start.

But the same applies to performance today. If you ask it to optimize for performance, to use a profiler, to analyze the algorithms and systemically try various optimization approaches ... it will do so, often to very good results.

Except it often is the case that when you break down what humans are doing, there are actual concrete tasks. If you can convert the tacit knowledge to decision trees and background references, you likely can get the AI to perform most non-creative tasks.

Normal isn't a myth. The mistake people make is taking the mode as normal, or worse mistaking their own experience as normal. But humans generally do tend to have a range of common behaviors that a significant percentage of people fit into. And you probably can even predict it to a reasonable degree, if you have some other metadata to correlate which sub-group they might correspond to.

Normal in the sense of "you can model a distribution of human behavioral processes or outcomes" that encompasses, say, 95% of humans in a given culture or geography is very much a thing you can do. And I'd go as far as to say a large chunk of the mental bandwidth of the average person is running those simulation models just to operate in a multi-human-agent world.

(If you want to say we observe bimodal or other multi-peaked distributions in practices rather than "normal" ones, I will strongly agree, but that usually isn't the objection when people say "normal is a myth")

Yep.

ChatAI - show the top 50 online retailers by revenue in the US and note any that have credible new stories about quality control issues. Save all of them except StoreX and StoreY in your list you use for comparison shopping.

Or maybe another one, scan all my credit card purchases for all time that you have history and record all the stores.

Done. And plenty of third party sites (consumer reports, wirecutter, etc...) will do this kind of thing too. And you could perhaps transitively trust them - either view direct lists or just scraping the places they recommend.

And the average person doesn't need to figure this out ... skills encoding this will propagate.