Animals don't "work". Not atleast for their own sake. If there is enough green pasture and water around, they don't even migrate to other places. So if work is meant to provide food and shelter and if machines can ensure that, humans don't need to "work".
Wealth is only a reserve capacity to help future generations so that they don't need to work for their basic needs. But if machines ensure that too, then wealth itself, as a reserve, is unnecessary.
How many man-hours go into various parts of the advertising distribution chain? Though a certain fraction of that energy goes to connecting people with goods and services they might find valuable, most of it goes into shifting numbers around for people that already don't personally have to worry about money.
We don't need to find endless ways for people to spin wheels, but as long as we're worried about "jobs," we will. We just need to find the social structures to provide people with basic needs and reserve "work" for things that are vital to society or truly inspired.
just?
Until the machines aren't owned by anyone (or owned by everyone, take your pick on the phrasing), the owners of the machine have no need to keep you alive.
This take is basically "Don't worry, people like Sam Altman are looking out for us"...
These "needs" are sometimes enforced by the systems and government so that people don't stay away from the work and "economy" keeps churning. The housing prices could be a way to keep the people working for loan payments.
Instant foods, nursing homes for elderly, creches, roads, commuter trains - are all ways to have more workers and make them focused on work.
Of course, billionaires have other plans, and are the main obstacle in achieving any sort of social cohesion.
"Work" doesn't exist to keep people busy, it exists to keep them alive.
Even now the machine owners have enough power to change laws to their liking, bending governments and public opinion to their will.
The odd thing is that after the pandemic just showed what societies can enforce, somehow it all is forgotten again when it comes to who holds what power.
I can't wait to be kept in agistment by my overlords, fed on treacle and oats, ridden in circles once a fortnight, and shot when I break a leg.
[0] https://www.researchgate.net/figure/United-States-Farm-based...
Luxury horse living during the heyday of working horses and pit ponies, "horse power" wasn't left ideal for a fortnight.
> How many horses do you see now that the world
Personally, a surprising number perhaps, there's a pony club at the top of my street in town, and the area is still littered with horses and other livestock.
This isn't my area, but it's not dissimilar: https://news.ycombinator.com/item?id=45623799
Full size image: https://live-production.wcms.abc-cdn.net.au/a26664f6500a7c74...
Some may consider local LLMs to help with that as the power of LLMs would be more distributed. I think local LLMs would help marginally. Companies as an entity would still be better positioned to use these to their advantage vis a vis individuals.
So projecting into the future I still wonder if it won't become more challenging for individuals to make a living on average.
We will never automate all work so we with half of humanity doing nothing of value it will be a struggle for the people who do nothing of value to convince people to do work for them.
We can see it now where products dont target the people without money. There is no point because they cant give you any reward so instead you do your work for the people that can give you something in return. We can use the government to stimulate and balance this a bit but at a certain point the number gets to high and things collapse.
Human agency is real and powerful - unless humans want to automate all work, it won't happen.
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.
Your analogy isn’t necessarily wrong, but it might ignore the extreme importance of nurses. Many medical facilities are only staffed with permanent nurses, with doctors helicoptering in, from time to time, to take care of specific duties that may require certain licenses, or provide specific advice.
So lots of jobs for nurses.
Maybe for a very loose definition of medical facilities that includes assisted living facilities.
But for example in an ER, nurses come and go with very rapid turnover and it’s common to staff with temporary travel nurses.
> nurses tend to do most of the actual work
Techs, environmental services, phlebotomists, respiratory therapists, CNAs etc. probably do more of the “work” than nurses.
> highly experienced nurses actually taking up the mantle for many duties often done by doctors
Only if they go back to school and become a Nurse Practitioner or CRNA, but in that case they are no longer functioning as a nurse. Even then they are general operating under the direct supervision of a physician.
> Nurses are in far higher demand, than doctors.
Only in absolute numbers. It’s far harder to hire a doctor than it is a nurse. I know an ex-NFL player who works as a physician recruiter.
It may take vastly more training but on average a full annual physical provides less benefit on average than a 30 second vaccination requiring minimal training. Value creation and skill are wildly different things in the medical profession.
I spent some time in the military, and my expression of medics and nurses are mostly derived from that experience, where I'm referring to a nurse as just any warm body who is able to provide aid.
For professional nurses who might work in hospitals, I'm sure that many of them have significant knowledge and experience to be very effective in providing medical assistance.
There's a much bigger group of people building games with Unity than the number of people building complicated engines like Unity. Same for [insert Javascript framework here].
The sell was - Creating your apps was easier than before. You don't need to know any programming language. You don't need IT. You have a GUI and just drag and drop and visual your apps. Just fill the fields and voila your app is ready.
The criticism of the approach was that low codes apps might not be secure, unsuitable for large scale and critical apps, and lead to increase in unsupported apps by "shadow IT".
The same reasoning exists today for AI coding. Anyone can create apps, its not great for complex and mission critical apps, might not be secure etc. And lots of discussion like your post parsing the future too closely.
Low/no code apps have continue to grow. But many of the low/no code tool users are developers who use it to make their jobs easier.
While some might say - this time it is different. I believe we are currently we are the beginning of the cycle so everyone is excited to use their PowerApps shaped Claude Code/Codex to make their 100th budget tracking app but as time passes and edge cases are figured out the biggest users for AI are going to be software developers (and I believe they currently are the biggest users).
As for software engineering jobs just like before engineers will be expected to output more and faster. This has happened with every innovation from assembly compiler to IDE to low/no code ways of building.
The different levels of expertise exists even today and it will remain so.
Wishful thinking by the managerial class. At best they can vibe code but they can’t verify that what was written is correct.
Tests can't be exhaustive, while even a mediocre developer is likely to possess enough background knowledge to notice risks that a non-developer would not think to test.
People keep forgetting that we haven't reached AGI yet. These tools can still make serious and sometimes obvious mistakes. Not long ago, vibe-coded software could embed credentials directly. That particular blunder seems to have been addressed, but there is still no reliable way to tell an LLM to avoid every class of obvious blunder.
Heh. I wouldn't be so fast in calling this one, yet. It might go either way, or a combination of the two, who knows... Things are moving and progressing fast enough to at least be wary of, and keeping an eye on things. I wouldn't be surprised of any outcome, tbh.
On the one hand, PMs get to hone in a set of skills that include lots of juggling resources, bridging the gap between stake holders and people that execute, work with different layers of technical expertise, lots of back and forth and so on. Having to "call" a thing after talking to 5 people from 6 different PoVs is interestingly something that could make them quite good at using "AI". They're already used to working with "jagged expertise" so to say. And that's really close to what "agents" do today. You might get a session where claude/gpt/gemeni turns out a brilliant piece of technical artefact, or you might get an average piece of content that misses key important aspects that a "human" could see from a mile away.
On the other hand, LLMs do one thing quite well: they raise the floor of what "minimum effort" in a thing gets you. So things like language barriers, basic processes, procedures, etc. get elevated to a level where you can use these tools and be better off than not using these concepts at all. So a very talented engineer that previously had these issues, could now use LLMs to get better at auxiliary but "unimportant" aspects of integrated that technical experience into other places. In a "90% of the time people expect this to work like this" way, but with the floor being raised. One quick example of this would be a technically sound piece of software that now has bare-minimum ux/ui from this century, instead of "engineer GUI" aspect :)
Who knows where this all goes. Yesterday there was an article here about someone taking a bunch of languages, asking an agent to mix concepts from all of them and slop a "new uber language" design. Is it the ultimate language that many have tried before? 99% sure it's not. Or at least this one won't be. But there's a chance, with how many people can now prompt their way to a PoC quite quickly, that we eventually get something cool. No idea how that'd look like, but it's likely the "you'll know it when you see it" kind of thing.
In such a future there would be a handful of lucky well paid artisans, a healthy community of hobbyists, and the overwhelming population of the planet who would be perfectly content to delegate their entire software diet to generative superplatforms that script themselves to perform any arbitrary software function. The idea of paying for individual bespoke software programs would become an anachronism for an era where software was so difficult to produce that entire teams spent years painstakingly tweaking programs to spec.
I'd like to imagine that it's ultimately going to work out for humanity to be in a better condition overall if that happens.
However, if there reaches a level of near or full autonomy in all aspects of knowledge work, then there is a strong possibility that the field with the highest growth potential is going to be in "Private Security"; as those who have access to the most resources seek to defend their own positions in a societal return towards aristocracy and serfdom.
Let's hope not though.
Yes, but this might also be a counter-point to your position. In a world of rising baselines, having a "pot but without all the bells and whistles" might be a thing people need. Instead of having a pot that holds fluids at every conceivable angle with 20 temperature thresholds, 5 versions that hold liquid in a cloud for you, with monthly subscriptions, having the ability to get a "like a pot but make it left handed and only holds sand because this is what I need" could turn out to be something that people want/need/end up chasing.
In other words spec down, not up, and base + my particular kind of a pot.
It's just hard to design robots that can handle patients that may be simultaneously fragile, mentally handicapped and aggressive in a way that doesn't hurt them and respects their rights. It can take multiple human nurses to do a seemingly simple thing like changing a diaper.
> 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.
Nursing and being a physician aren't really the same thing at all, and they require different skill sets, it's not just "having more knowledge". Just because someone is an amazing surgeon doesn't mean they would also make a good nurse.
> 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.
I think you just described a staff swe
> 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.
These people already exist. They are the business analysts who know SQL and maybe Python, R, or VBA. Marketing people who work on Wordpress landing pages. People doing systems integration, the IT department, sales engineers, and on, and on, and on.
> 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.
You said it, no code/low-code has existed forever.
I think many people will wish it was like this. But when AI becomes so capable that a nobody who doesn't understands computers a well as a "doctor" uses AI to create something BETTER or superior or just as good then employers will think... why am I paying that "doctor" more than that nobody?
See right now everything is fine, because AI is not that good yet. But if it gets better. Well. The future will be one where we trust AI more and more.
The medical field is also going to change though. Massively. Because people are going to realize you don’t need to pay someone $400k per year to hand out advice about moderate exercise and which antibiotic is appropriate for a sneeze-cough with yellow mucus.
Regulation isn’t going to prevent this. AI is already way too easily accessible to ever rein it in again. Not to mention that the US now has serious competition from a hostile country, so they can regulate their own AIs all they want without it making a difference in practice.
Who is going to realize that?
The same forces that prevent you from walking into a pharmacy and asking for antibiotics based on what you found on WebMD will prevent you from doing it with a ChatGPT printout in hand. Lawyers and doctors are the best-known examples of industries that are in control of who gets admitted to practice the profession.
So I think it would be more comparable to something like literacy. There was a time when that was a fairly uncommon and highly valued skill. Now the guy flipping burgers or pouring a cup of coffee is also almost certainly fully literate. And in fact many jobs have evolved in a way such that it became mandatory, but only because it was already ubiquitous. I expect to see the same thing with software. The industry of producing software that do fairly simple tasks will probably die, but in its place will be a vast array of heavily customized and oft iterated software for companies and people achieving their own stuff.
The mobile industry is a perfect example of where this will be massive shift. Right now there's a million mobile apps to execute extremely basic functionality on phones, but it's loaded with advertising, begging, and general annoyances. As are the app stores themselves. When you can make software that does that in a few minutes with a single prompt, and people realize this (as we're already practically at this point), then that will be the end of those apps. This is because the one thing LLMs have shown is that natural language interfaces are way less friction than using search, whether on the web or an app store. And so there will be a time when it will be lower friction to simply just quickly build your own app to do [whatever] than dealing with somebody trying to monetize an alarm clock.
I don’t understand how people can say this and then continue talking about software. So we’re saying machines can now casually do complex and cognitively demanding jobs like software development (or 90% of all white-collar jobs out there) and we’re NOT worried about the lynching mob going door to door and hanging IT people on lampposts? And I’m being serious, the impact this would have on societies would be unprecedented.
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.
This is true as a sentiment, but my understanding is that the majority of students are overwhelmingly using AI for ~everything. If a thing provides massive utility people will use it.
But are they also paying for it? Or simply using the free version because it's available?
Garbage in, Garbage out.
The University market is brutal too. If you aren't using AI too, you are falling behind. Many see it as a means to an end.
Well, one thing about AI... if it does become our overlords, maybe it won't be so eager to be wheedled into giving passing grades. :/
Have you read the research that says AIs are more likely to react favourably to output based on their own model compared to those of a different AI model? Guessing teachers subconsciously grade similarly, like people who use one model get more of some grade than people who use another one...
Guessing this is also why so many liberal arts majors are being cut.
I 'sorta' get why people might use AI in a required class though I am not for it, but why major in something and do it? I mean aside from wanting money (and, really, many of those majors don't make much).
Very open definition of sabotage.
Everybody says they hate heroin but once you try it, you can't get enough of it.
What upset me a bit were phrases like “This is not a slogan. It’s a framework” which immediately devalued the work for me.
I have read so much Ai generated text recently, that I developed some AI-fatigue or AI-burnout, and I’m wondering if that might hit more fields - making more humans reject Ai work.
To be clear, I still like the text and I don’t know if it was written (partially) by Ai or not - but it’s this uncanny feeling I got reading it.
Why? Because it resembles the typical "You're not just implementing a text editor, you're reshaping the text editing landscape"?
I cant read this shit anymore.
"creating cross functional AI evaluation team to keep the company honest"
Fucking garbage.
I have an old book between me and the keyboard, and just read it while the AI is thinking, so I can read non AI words.. otherwise its like reading books by the same author over and over and over again.
I will go touch some grass now.
When lawyers and writers are talking to me about "docker containers" and "agents" I assure you that the amount of code out there is going to grow.
It pushes the bulk of the work to review. So teams with good practices can account for this.
For junior teams, the time saved is massive, because they aren't doing all the other practices required to prevent technical debt.
But it's at my day job, and it's because I was able to write a prompt which automates having Copilot review uploaded scanned PDFs of invoices with checks (and the bank line obscured with a pen, so no PII) and then write a batch file which renames the files per a file-naming convention, removing the need to open them in batches of 50, find the Invoice ID, re-save using that filename, then quit and re-launch Adobe Acrobat (if left running, eventually I run into a bug where it stops saving files), then run a .bat file which renames based on Invoice ID as a filename.
Problem of course is I've been running into a limit of number of allowed files per 24 hr. period.
Even if it's not less work, it feels like less effort.
I can now write software quicker in most of the cases, but the rest of the organization moves as slowly as ever.
The problem is they are now paying me more, plus paying for the cost of using the AI, and the needless complexity also slows down the employees. So more costs there as well, any future debugging is going to cost far more and at the end of the day they are getting less quality on the core function but far more presentation data that is essentially meaningless.
For example, all the work like translations that used to be done by humans, now it is a CMS AI feature.
Secondly teams setup.
It used to be we did everything ourselves for development, then cloud, SaaS products and serverless decreased the teams size required for delivery.
Now with AI, there is an even greater push for low code/no code tooling, with agents, leaving the actual programming left for MCP tools that might not yet be available for the project.
Thus you get a team of five doing what used to be about 15 a decade ago.
I didn't do fewer hours in these weeks but had time to explore and innovate a little.
> It’s funny. I was looking at my GH activity graph. It’s been pretty solid green, for years. I stay busy.
> But since I’ve been using an LLM, it’s been bright green.
> I always check in code manually. I don’t let the LLM do it.
Once you've used a BBS or modem, "online banking" is an obvious idea - just a very difficult one to implement until you add on decades of security and improved connectivity.
But also, the article is explicitly arguing against armageddon.
- i would assume it is reasonable that anyone comes and see what other posts a person has written except you cant find that page anywhere linked
https://www.reddit.com/r/gifs/comments/3p0b3i/graphic_design...
- 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.
But we already do have have some kind of measurement of most of these types of side factors, and they actually aren't at zero and are increasing rapidly. So the implication that they will not be human level until decades from now is just (hopeful?) speculation or fuzzy thinking.
To me this looks like a really academic and official sounding version of the same quasi-religious hopium that usually defends the sanctity of the human. He is essentially saying that there is just something so special about humans that it will never be reproduced in a machine. It's very similar to dualism (and in many people actually is religious dualism). No AI is going to have human creativity or judgement. Not anytime soon. Why? Well, we all just _know_ that's not possible. Okay, maybe in a couple of decades (but they don't necessarily believe that anyway). Why would that take decades? Well we all can just _tell_ it's no where close, right? Because AI of today just isn't special like humans.
Aside from that worldview issue, I think that people still are not taking seriously or internalizing the concept of exponential improvement.
Computing efficiency gains can actually level off. In fact, they have many, many times before. But they always tilt back up again when we invent the next approach to get beyond the current level. This is how it has been for 90 years.
There are multiple ways that we continue to see huge gains in AI software, architecture, and hardware. There are huge efficiency gains available still as we move towards more radical fully compute in memory and/or analog approaches and other options like models implemented in hardware.
My mother worked in an office in London as a shorthand typist in the 60s, along with thousands of other young women.
At some point computers began to enter offices, bosses typed their own letters and then emails, and this category of job simply evaporated. Of course there was still SOME secretarial work, and some workers retrained to do it, but most simply had to leave the sector.
Isn't that a common story with technology replacing workers?
There will always be new, hard problems to work on. AI will not, and can not eliminate that.
> 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 ?
I would doubt however that this would be an 'Equals' or 'Implies' scenario. Let go of seeing either of them as binary, and then not even as scalers.
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...
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.
Does he want to fund the arts? Humanities?
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.
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.
Depends on what kind of game you are building. I can tell you that even Claude Opus absolutely hates desync bugs and has a rather hard tracing them. Maybe Fable or chatgpt-5.6 are better?
The only question is what next?
Our only hope is to teach the AI to meld with our bodies and use them for gestation, energy or hibernation. The alternative is sustenance.
If AI is subject to private ownership in a competitive market between competing suppliers, it will be like better cars, we’ll just drive faster.
Power consumption will be a limiting factor in those countries relying on intermittent, weather dependent power generation with no base load. Especially if users prefer Apple’s privacy first AI on edge devices.
Hopefully in western countries it can encourage more young women to bear three children before they turn 35. Young men have to pick up their game and create an environment to redirect their suicidal empathy into more productive pursuits.
“Where can you find another non-linear servo-mechanism weighing only 150 pounds and having great adaptability, that can be produced so cheaply by completely un-skilled labour?” - Albert Crossfield 1954