- Work is shifting from building/doing to evaluating, judging, and steering — that's where human value will concentrate.

Other supporting points. ------

- No lab milestone or "RSI breakthrough" will suddenly eliminate jobs — economic impact unfolds gradually over decades.

- Reliability, not raw capability, is the real bottleneck holding back AI automation today.

- Historically, making work cheaper/faster (ATMs, radiology, coding) has grown employment, not destroyed it.

- Superintelligence claims misunderstand human intelligence, which is itself amplified by tools like AI ("co-superintelligence").

It is not a good idea to compress articles like this but there are many of these opinions to read and trying to get to the point quickly to uncover new viewpoints.

> A battle of two narratives > Build wealth before AI obviates our skills > Build skills, agency, taste, judgement

both narratives are portrayed as being odds with each other but, I can't come up with a single "build wealth" scenario that doesn't involve building skills, agency, taste and judgement.

what am I missing ?

So if things continue as they are today, I think in the near future, being a software developer is going to be more analogous to the medical field, where in the medical field you have different levels of professional expertise.

Some will be like nurses, and some will be closer to a medic and a smaller set will be like doctors. Each with increasingly required knowledge and experience to fulfill a needed role.

Those who used to be actual software developers are going to be (or have to become) more in the doctor role with years of internship and practical experience to be the architects guiding the overall AI implementation of software development in organizations.

The medics are going to be people who are semi-technical, where they have some technical understanding but they don't dedicate themselves to it, like say product managers, where they jump in to help development along, but don't need to have many years of experience or very deep technical knowledge.

At the nurse level, it's probably going to be similar to what people would do in the past with no code tools, where somebody in marketing who knows very little to nothing about coding at all is just going to directly converse with AI systems, but they'll never be likely to get anything more advanced than the tools they could think up for themselves.

Of course, it's so hard to tell what the next big discovery or changes to the nature of world society might push things in one direction or another.

AI can slop fork or clone existing software well, but a clone of an existing game is pointless, it's basically guaranteed to be derivative and worse than the original game, and games aren't so expensive that you can't just buy the original. AI can't know if new mechanics or angles to an existing genre will feel good to play, or if a new genre is fun, that requires a human to experience the game in its totality.

Games are also very resilient to sloppy AI coding, and if an indy game crashes nobody is getting paged.

If you think it is different, just think of how many people write books professionally, or even publish online.

Once the noise settles down a bit and boardroom shakes off their delusions as you can see in rehiring in Ford and Zuck who was very bull on AI remark about "not being it". It will be just the same, but different.

Ford: https://www.bbc.com/news/articles/cgrkd41n2v9o IBM: https://qz.com/companies-rehiring-workers-ai-layoffs-automat...

However, this following quote has a simple reason that I don’t see anywhere in the article or framework:

“”” Why is there a huge gap between what people in various occupations could be using AI for and what they’re actually using it for? One reason could be that people are slow to adopt technology, and that’s certainly part of our framework. “””

I would like to add a reason: that the Silicon Valley companies who developed the LLMs are brigands: cognizant of their actions, they have stolen (and continue to steal) the world’s copyrighted material and are selling it back to the masses and the politicians as if they are the arbiters of information itself.

Specifically responding to the quoted question, I could be using Claude or ChatGPT or Grok or DeepSeek or any other to have come up with this comment, or to write emails, or to implement my Python for me, etc., but I use none of them for anything. Doing business with brigands is a choice, and a choice that I hope becomes less and less palatable so that the financial, political, social, and moral fever that is our zeitgeist finally breaks.

According to WRITER’s 2026 Enterprise Adoption Survey, 44% of Gen Z employees admit to sabotaging their company's AI strategy in at least one way compared to 29% of employees overall.

Sabotage behaviours include entering proprietary information into AI tools, using non-approved AI tools, refusing to use AI tools or outputs, ignoring guidelines or best practices, intentionally generating low-quality outputs, refusing to take AI training and tampering with performance metrics to make AI appear to underperform.

I sort of worry about things like AI figuring out scripts so well that even multi-tier support work is gone. And learning how to write fiction or create foods so in accordance to our tastes (sugar, fat, etc with food, exactly what each of us is interested in, with writing) that we even lose those truly human creative jobs. Might not ever wanna leave those bubbles.

So much of the human drive is exploration and why and what if. Assuming everyone in the world can have no money problems, what will AI not be able to figure out? Will we enjoy the equivalent of a major breakthrough if an AI solves it in five minutes, or just the outcome? Why learn things?

AI could be a horrible jailor. And better at cancelling than any perhaps sager Gen Z or millenial. Bears some caution to be wary of this and where that power sinkhole will go.

But then, I still think the previous AI winters were more a result of sense and caution than most of us know, and we cannot fathom our species' ways of reasoning/thought processes the way we did as a species thirty, fifty, eighty years ago. Erring on the side of caution is not a terrible thing.

I mean, I have worked and work with AI, but it seems weird for us as a species not to have placed guardrails to prevent us from wiping one anothers' careers and relationships out. What will we talk about? If our generative AIs should be allowed to date?

Again, I am assuming a fast, though not sudden, acceleration that would compound, and sooner than most probably think.