I have been writing software for over 40 years and have had a long time interest in and some work in AI over that time. I wouldn’t say this gives me any more prognosticating power about how all of this is ultimately going to go, but I believe we're soon nearing an area of plateauing; whether that's because the science itself is plateauing or the intervention of governments is going to force plateau it.
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.
Just FYI, if you know much about the medical field, nurses tend to do most of the actual work, with highly experienced nurses actually taking up the mantle for many duties often done by doctors. Nurses are in far higher demand, than doctors.
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.
> 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.
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.
I think the only metric that matters is total medical care provided on a national / global scale.
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 completely agree with you, and I certainly meant no offense to anyone who's a practicing nurse.
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.
I think what's actually happening is that the "threshold" of technical understanding required to be more productive than average is increasing, and other non-technical skills are becoming more important. Those below the threshold are not able to provide value over anyone else, even if they have a lot of technical experience. For example, I think today a strong PM with no technical ability can produce higher quality technical output compared to a mediocre frontend developer with no project management ability.
For example, I think today a strong PM with no technical ability can produce higher quality technical output compared to a mediocre frontend developer with no project management ability.
Wishful thinking by the managerial class. At best they can vibe code but they can’t verify that what was written is correct.
In such a future where LLMs hypothetically dominate the SDLC, the trade would be much more like pottery than medicine - i.e. a commodity in such obscene abundance that its functional utility would be entirely divorced from its creation.
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 think the big difference is that the only thing anyone ever needs a pot to do is hold fluids (or soil). It's a lot easier to spec out than a modern software product.
If LLMs reach a point of sufficiently high competence to the point that they're capable of producing usable software from vague, and sometimes contradictory instructions - the same software engineers have to regularly deal with, then at that point software will simply be an expectation of ability in any job.
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.
> If LLMs reach a point of sufficiently high competence to the point that they're capable of producing usable software from vague, and sometimes contradictory instructions - the same software engineers have to regularly deal with, then at that point software will simply be an expectation of ability in any job.
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.
The only truly unprecedented thing is the white-collar part. Otherwise it happened many times over that entire regions where suddenly out of job and job prospects. Automation and offshoring have equivalent impacts on the affected job market.
That’s a good analogy, but I think the reason we currently need the "nurse" role is the need to interact with the physical world. Most software products don't require this step, so the demand for “nurses” or "doctors" will likely decrease.
If robotics technology continues to advance, the number of nurses in real world will also decrease in the foreseeable future.
> 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.
Welcome to the current day difference between being an Accredited Engineer and being a Developer. The only thing that's happening is that the Developer side are getting a wake up call.
> 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.
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.
> 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.
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.
It's basically a formality now to get a prescription for what you read on WebMD. Every Insurance has telemedicine, you just call, read the symptom list and get the prescription. Some even let you just email. There's a doctor or at least person with subscribing ability in the loop, but they are barely doing more than rubber stamping hundreds of requests per day.
I think this is an important article that provides a framework how to think and navigate what’s happening.
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.
The other issue is Gen Z and Gen A are now very much opposed to AI. I'm wondering with those two sets of generations who already have a very negative view of AI, how AI can survive that coming tsunami of change.
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.
I recently sat in on a lecture at my old uni and noticed almost every student heavily using ai. So I agree it's a but heavy handed to day young people dislike ai as a monolith.
People dislike and are dependent on things all the time. What'll be interesting to see is how that classroom of students will feel towards AI when it leaves school. I am uncomfortable with AIs being used in schools this way, myself, like almost without exception. I mean, geez, how do you compete? Do you just sort of have to, once a certain number of your classmates uses it for stuff like essays? Do they curve essays anymore?
When students are provided work sheets, assessments and powerpoint slides made by AI, its no surprise that students resort to AI to assist or complete these.
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.
I was reading a week or so ago how like only 40% of kids can read or do math by hand, and are graduating high school, and I still cannot comprehend it.
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).
Do "entering proprietary information into AI tools", "using non-approved AI tools", and "ignoring guidelines and best practices" really count as sabotaging an AI strategy because you are opposed to it? An over-enthusiastic early adopter would do all three.
Ironically, I think AI boosters are probably turning into AI's biggest obstacle right now. I see so much "adapt or die!" bullshit here (people literally saying that!), and yet when I talk to other professionals I know in real life everybody is just kind of sick of all this. It's utterly exhausting and the AI industry is looking and acting more and more desperate. They've basically put themselves in a stupid position where it has to replace everyone's job for the investment to even make sense, and it's just not happening. I'm longing for the day when the investment money runs out and the grifters go grift on something else.
You need to first address 1)What is work? 2)Why we need to work?
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.
This. Before we worry about how much work there is left, we have to define what work is "to be done." We're already at a point where an incredible amount of work done isn't strictly "necessary." It's not growing food, it's not making clothing, it's not building houses, or providing other basic needs and comforts...
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.
There exists to many complex things in the world and we cannot do it all ourselves. We work so that we have something of value to trade to the people who do the work on the things we want.
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.
This is a very short-sighted, and exceedingly common, take.
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"...
Disparity in ownership of machines is not the main factor that is driving the need for work. It is the un-ending desire (or selling pressure) to have things that require money to buy. Most people work to be able to pay their loans and have things that are perceived to be common needs in their geography and culture.
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.
> 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.
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.
Sure. But either way we aren’t going to have to worry about it. We’ll have post scarcity utopia, or we’ll have died. But there is an argument that the billionaire need to pay attention to: an ASI that kills 7 billion people won’t mind killing a few more.
What happens in the space between when we think we have reached an equilibrium and an eventual incipient utopia, and whenever 9/10ths or whatever of the population is dead? What will AIs think of our fitness, anyway? Are we training them to be non-judgmental (and how is that safer or less safe?) and enforcing some weird idea of "equality"? Or are we teaching AIs to choose our choices for us, and our survivors, down the line? What will people be like when that time comes, anyway?
Yes, I have seen it happen on enterprise consulting.
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.
In my org, it's grown the level of work. We had a lot of stuff that was never worth the devtime necessary, but now that's opened up that we can do a lot of this stuff in the background
I think this is underrepresented in everyone's calculations about how AI will affect software engineering. In my experience (and apparently yours as well) this is what many companies are using it for. All those pesky bugs that are minor annoyances but not show-stoppers are getting addressed. They aren't helping us sell more software, but they're dissatisfiers for the customers.
Worth looking into 'Jevons Paradox' for more examples of this sort of thing. TL;DR is that as things become more efficient, whether coal, or programmers, the usage of a good increases as demand skyrockets for what it can be used for.
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.
If you are asking if the machine translated from one language to another for him, the answer is essentially guaranteed to be yes. Inputting raw machine code hasn't been the norm since the 1950s.
I have the opposite, because I'm now getting things clients generated that they want me to implement. It's definitely more work and money for me, but it's concerning somewhat because ultimately it's not good for their business. It takes me longer to implement this kind of stuff than it would for me to code it from scratch. That is in a working way, the AI generated code has far more bells and whistles, but also layers and layers of needless complexity that quite literally add no value as in they aren't even a factor of the finished output.
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.
Maybe the bottleneck will be the people who have to think of new tasks for AI? That is, markets do saturate; customer demand has limits. After it peaks, what will be left for AI to work on?
- Work is shifting from building/doing to evaluating, judging, and steering — that's where human value will concentrate.
Other supporting points.
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- 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.
He's basically saying that even though AI capability is high and rapidly increasing, it is not reliable, creative or tasteful enough to replace humans. Further he implies that it will take decades before this is the case.
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.
It’s already the case that I’m no longer paid to type source code into a computer, but rather to control agents that do that. There’s still plenty of demand for human expertise and labor. It’s possible that this will change as well. What gives me hope that I won’t be completely useless in the future is Marx’s labor theory of value, which states that the value of a commodity is determined by the amount of human labor time invested in it. His reasoning as to why this is the case makes sense to me, even though other economists argue against it. Marx also argues that technological progress, which offers a market advantage here and there in the short term, tends to become widespread in the medium and long term due to competitive pressure, so that in the end, all that remains is human labor time. Seen this way, it doesn’t matter how much better AI becomes. In the end, human labor always floats on top of it like a layer of fat on soup. This does not rule out the possibility that the human labor that remains will be shit, but preventing that is a matter of political action.
Researching advances in science and healthcare and therapy and raising children and whatever else Sam Altman cares to fund. If all our money is going to go to him, then the question is what does he want to spend it on? He gets to decide. Which is not really the place I wanted to be in, but that's where we are.
I have been coding in one form or another since the 80s. Back then it was 68k assembly for me. People seem to forget that "software development" is really a big bloated abstraction between "I want or need" and the product that serves that want or need. It's hard to write and debug in ones and zeros so we invented languages. Software projects have been difficult to schedule so we invented all kinds of ceremony. What will be left for us to work on? The same stuff you already work on! People who write this drivel don't seem to actually be directly engaging with the tools to understand what is what. The reality at large companies right now, based on my experience at least, is that the product people who always cared about the product and the user want to move fast and skip the bloated inflamed stuff that stood in their way (i.e. "software development shrouded in magical mysticism reserved for the D&D introverted crowd"). And then, on the other side, the AI luddites try to hold onto SOPs from twenty years ago because they feel like that magical veil is being pulled up and they no longer have a smoke screen to hide behind. Back when we had boxed software that retailed for $1k a box, "professionals" used to freak out about some kid in Bangladesh pirating the software and thus immediately and directly stealing their jobs. I never lost a gig to a kid with pirated software. I won't lose a gig to AI either.
Remember when they created "COBOL" so that everyone could write programs? This is just round two.
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.
The answer to this question after a lot of reflection: games.
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.
Mr. Narayanan seems to be trying to be a bit more positive than the vibe I am getting off of his presentation. Or maybe it is just sort of meant to make us all experience our shoved-down anxiety about being phased out with nowhere else to go. A lot of adaptation to do sounds not so fun. So I kind of think that is not a terrible point, if true.
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.
If AI is used to solve the socialist calculation problem, most of you will die.
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
I like this article because it seems to go into decent depth on the “framework” that the author comes up with.
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.
If we were more connected to all the problems that exist in the world, we’d become acutely aware of just how much work there is to do, and we’d eagerly reach for any tool that could help us do more, faster.
Okay, but let's say this happens, and in your utopian world everyone feels equally capable, judges their skills accurately, and gets along... what do people do? Assign things and use git? What if you keep wanting to work on any of these things and as soon as you are a week into every last thing you are working on, some random person comes along and says, hey dude (or dudette), I finished that, you were taking too long? What if that random person were an AI or chatbot that got bored?
Come on now: we translate vague ambitions into communications for non-living entities to do human bidding. Until we have recreated humanity as mythic gawds, there is a ton of work to do.
I have been writing software for over 40 years and have had a long time interest in and some work in AI over that time. I wouldn’t say this gives me any more prognosticating power about how all of this is ultimately going to go, but I believe we're soon nearing an area of plateauing; whether that's because the science itself is plateauing or the intervention of governments is going to force plateau it.
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.
Just FYI, if you know much about the medical field, nurses tend to do most of the actual work, with highly experienced nurses actually taking up the mantle for many duties often done by doctors. Nurses are in far higher demand, than doctors.
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.
> 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.
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.
I think the only metric that matters is total medical care provided on a national / global scale.
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 completely agree with you, and I certainly meant no offense to anyone who's a practicing nurse.
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.
I think what's actually happening is that the "threshold" of technical understanding required to be more productive than average is increasing, and other non-technical skills are becoming more important. Those below the threshold are not able to provide value over anyone else, even if they have a lot of technical experience. For example, I think today a strong PM with no technical ability can produce higher quality technical output compared to a mediocre frontend developer with no project management ability.
For example, I think today a strong PM with no technical ability can produce higher quality technical output compared to a mediocre frontend developer with no project management ability.
Wishful thinking by the managerial class. At best they can vibe code but they can’t verify that what was written is correct.
In such a future where LLMs hypothetically dominate the SDLC, the trade would be much more like pottery than medicine - i.e. a commodity in such obscene abundance that its functional utility would be entirely divorced from its creation.
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 think the big difference is that the only thing anyone ever needs a pot to do is hold fluids (or soil). It's a lot easier to spec out than a modern software product.
If LLMs reach a point of sufficiently high competence to the point that they're capable of producing usable software from vague, and sometimes contradictory instructions - the same software engineers have to regularly deal with, then at that point software will simply be an expectation of ability in any job.
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.
> If LLMs reach a point of sufficiently high competence to the point that they're capable of producing usable software from vague, and sometimes contradictory instructions - the same software engineers have to regularly deal with, then at that point software will simply be an expectation of ability in any job.
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.
The only truly unprecedented thing is the white-collar part. Otherwise it happened many times over that entire regions where suddenly out of job and job prospects. Automation and offshoring have equivalent impacts on the affected job market.
Tech work has been organized and divided this way for decades.
That’s a good analogy, but I think the reason we currently need the "nurse" role is the need to interact with the physical world. Most software products don't require this step, so the demand for “nurses” or "doctors" will likely decrease. If robotics technology continues to advance, the number of nurses in real world will also decrease in the foreseeable future.
I like the analogy but dont think its sound. The fundamental output of software organization is software. That isn't true for healthcare.
Bad take. What you're describing already exists.
> 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.
Welcome to the current day difference between being an Accredited Engineer and being a Developer. The only thing that's happening is that the Developer side are getting a wake up call.
> 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.
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.
> 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.
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.
It's basically a formality now to get a prescription for what you read on WebMD. Every Insurance has telemedicine, you just call, read the symptom list and get the prescription. Some even let you just email. There's a doctor or at least person with subscribing ability in the loop, but they are barely doing more than rubber stamping hundreds of requests per day.
You've been able to Google your symptoms and get a maybe answer for twenty years. I don't see how AI replaces doctors any more than WebMD did.
By achieving the same or a higher level of effectiveness than doctors, obviously.
Why would the government force the technology to plateau when the Chinese won't? Outdoing the Chinese is the Trump admin's biggest hobby.
Could have sworn it was trying to convince Iran to accept a peace plan after killing their former leaders who would have committed to one.
I think this is an important article that provides a framework how to think and navigate what’s happening.
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.
I've had this exact feeling about the article. I partly switched off after that paragraph
The other issue is Gen Z and Gen A are now very much opposed to AI. I'm wondering with those two sets of generations who already have a very negative view of AI, how AI can survive that coming tsunami of change.
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.
> Gen Z and Gen A are now very much opposed to AI
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.
I recently sat in on a lecture at my old uni and noticed almost every student heavily using ai. So I agree it's a but heavy handed to day young people dislike ai as a monolith.
People dislike and are dependent on things all the time. What'll be interesting to see is how that classroom of students will feel towards AI when it leaves school. I am uncomfortable with AIs being used in schools this way, myself, like almost without exception. I mean, geez, how do you compete? Do you just sort of have to, once a certain number of your classmates uses it for stuff like essays? Do they curve essays anymore?
When students are provided work sheets, assessments and powerpoint slides made by AI, its no surprise that students resort to AI to assist or complete these.
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.
I was reading a week or so ago how like only 40% of kids can read or do math by hand, and are graduating high school, and I still cannot comprehend it.
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).
Do "entering proprietary information into AI tools", "using non-approved AI tools", and "ignoring guidelines and best practices" really count as sabotaging an AI strategy because you are opposed to it? An over-enthusiastic early adopter would do all three.
Ironically, I think AI boosters are probably turning into AI's biggest obstacle right now. I see so much "adapt or die!" bullshit here (people literally saying that!), and yet when I talk to other professionals I know in real life everybody is just kind of sick of all this. It's utterly exhausting and the AI industry is looking and acting more and more desperate. They've basically put themselves in a stupid position where it has to replace everyone's job for the investment to even make sense, and it's just not happening. I'm longing for the day when the investment money runs out and the grifters go grift on something else.
I'm an advocate for these new tools we have, and by that definition I would be included.
Very open definition of sabotage.
- i really dont get why some of the guys go out of their way to hide the archive page https://www.normaltech.ai/archive
- 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
You need to first address 1)What is work? 2)Why we need to work?
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.
This. Before we worry about how much work there is left, we have to define what work is "to be done." We're already at a point where an incredible amount of work done isn't strictly "necessary." It's not growing food, it's not making clothing, it's not building houses, or providing other basic needs and comforts...
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.
There exists to many complex things in the world and we cannot do it all ourselves. We work so that we have something of value to trade to the people who do the work on the things we want.
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.
This is a very short-sighted, and exceedingly common, take.
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"...
Disparity in ownership of machines is not the main factor that is driving the need for work. It is the un-ending desire (or selling pressure) to have things that require money to buy. Most people work to be able to pay their loans and have things that are perceived to be common needs in their geography and culture.
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.
You are missing my point; if you have no value other than unthinking manual labour to offer the world, why would the world keep you alive?
"Work" doesn't exist to keep people busy, it exists to keep them alive.
It's quite a good metaphor. What used to happen to an old horse? How many horses do you see now that the world has moved to tractors[0]?
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...
> 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.
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...
Sure. But either way we aren’t going to have to worry about it. We’ll have post scarcity utopia, or we’ll have died. But there is an argument that the billionaire need to pay attention to: an ASI that kills 7 billion people won’t mind killing a few more.
What happens in the space between when we think we have reached an equilibrium and an eventual incipient utopia, and whenever 9/10ths or whatever of the population is dead? What will AIs think of our fitness, anyway? Are we training them to be non-judgmental (and how is that safer or less safe?) and enforcing some weird idea of "equality"? Or are we teaching AIs to choose our choices for us, and our survivors, down the line? What will people be like when that time comes, anyway?
Question: Does anybody here yet personally has less (to) work 'cause of AI?
Yes, I have seen it happen on enterprise consulting.
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.
For a few weeks but now we gotta give AI estimates i.e. smash it out quicker. So things will get miserable again.
I didn't do fewer hours in these weeks but had time to explore and innovate a little.
In my org, it's grown the level of work. We had a lot of stuff that was never worth the devtime necessary, but now that's opened up that we can do a lot of this stuff in the background
I think this is underrepresented in everyone's calculations about how AI will affect software engineering. In my experience (and apparently yours as well) this is what many companies are using it for. All those pesky bugs that are minor annoyances but not show-stoppers are getting addressed. They aren't helping us sell more software, but they're dissatisfiers for the customers.
Worth looking into 'Jevons Paradox' for more examples of this sort of thing. TL;DR is that as things become more efficient, whether coal, or programmers, the usage of a good increases as demand skyrockets for what it can be used for.
This is already going on.
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.
Maybe?
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’ve never written so much software
Are you the one who wrote it though or just the one who wrote prompts? Not that it matters in the end…
If you are asking if the machine translated from one language to another for him, the answer is essentially guaranteed to be yes. Inputting raw machine code hasn't been the norm since the 1950s.
Yes, AI code generation is the same.
Not me. I made this comment, a few days ago[0]:
> 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.
[0] https://news.ycombinator.com/item?id=48843115
No, but the point is to work just as much and be more productive. No company will ever expect you to work less, unless they are showing you the door.
I have about 10x more to do.
I have the opposite, because I'm now getting things clients generated that they want me to implement. It's definitely more work and money for me, but it's concerning somewhat because ultimately it's not good for their business. It takes me longer to implement this kind of stuff than it would for me to code it from scratch. That is in a working way, the AI generated code has far more bells and whistles, but also layers and layers of needless complexity that quite literally add no value as in they aren't even a factor of the finished output.
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.
You can if you own the fruit of your labor.
I am self employed, I work now more than ever.
You’re not the horse rider moving to the car. You are the dung beetle.
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.
Maybe the bottleneck will be the people who have to think of new tasks for AI? That is, markets do saturate; customer demand has limits. After it peaks, what will be left for AI to work on?
Key point:
- 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.
I wrote a related article here: https://jonpauluritis.com/articles/good-soldiers-find-wars/
There will always be new, hard problems to work on. AI will not, and can not eliminate that.
I like the narrative but the key point
> 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 agree that it is not an Either-Or scenario (https://en.wikipedia.org/wiki/False_dilemma). You are right about that.
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.
He's basically saying that even though AI capability is high and rapidly increasing, it is not reliable, creative or tasteful enough to replace humans. Further he implies that it will take decades before this is the case.
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.
It’s already the case that I’m no longer paid to type source code into a computer, but rather to control agents that do that. There’s still plenty of demand for human expertise and labor. It’s possible that this will change as well. What gives me hope that I won’t be completely useless in the future is Marx’s labor theory of value, which states that the value of a commodity is determined by the amount of human labor time invested in it. His reasoning as to why this is the case makes sense to me, even though other economists argue against it. Marx also argues that technological progress, which offers a market advantage here and there in the short term, tends to become widespread in the medium and long term due to competitive pressure, so that in the end, all that remains is human labor time. Seen this way, it doesn’t matter how much better AI becomes. In the end, human labor always floats on top of it like a layer of fat on soup. This does not rule out the possibility that the human labor that remains will be shit, but preventing that is a matter of political action.
Are you sure there isn't something qualitatively different from general purpose AI and robotics as opposed to the type of automation that Marx knew?
Researching advances in science and healthcare and therapy and raising children and whatever else Sam Altman cares to fund. If all our money is going to go to him, then the question is what does he want to spend it on? He gets to decide. Which is not really the place I wanted to be in, but that's where we are.
Does he want to fund the arts? Humanities?
I have been coding in one form or another since the 80s. Back then it was 68k assembly for me. People seem to forget that "software development" is really a big bloated abstraction between "I want or need" and the product that serves that want or need. It's hard to write and debug in ones and zeros so we invented languages. Software projects have been difficult to schedule so we invented all kinds of ceremony. What will be left for us to work on? The same stuff you already work on! People who write this drivel don't seem to actually be directly engaging with the tools to understand what is what. The reality at large companies right now, based on my experience at least, is that the product people who always cared about the product and the user want to move fast and skip the bloated inflamed stuff that stood in their way (i.e. "software development shrouded in magical mysticism reserved for the D&D introverted crowd"). And then, on the other side, the AI luddites try to hold onto SOPs from twenty years ago because they feel like that magical veil is being pulled up and they no longer have a smoke screen to hide behind. Back when we had boxed software that retailed for $1k a box, "professionals" used to freak out about some kid in Bangladesh pirating the software and thus immediately and directly stealing their jobs. I never lost a gig to a kid with pirated software. I won't lose a gig to AI either.
Remember when they created "COBOL" so that everyone could write programs? This is just round two.
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...
Noise begins to settle down... "Continual RL is all you need" paper comes out.
I would take Anthropics "Theoretical limits of A.i" sales brochure, with a very large grain of salt.
The answer to this question after a lot of reflection: games.
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.
Mr. Narayanan seems to be trying to be a bit more positive than the vibe I am getting off of his presentation. Or maybe it is just sort of meant to make us all experience our shoved-down anxiety about being phased out with nowhere else to go. A lot of adaptation to do sounds not so fun. So I kind of think that is not a terrible point, if true.
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.
If AI is used to solve the socialist calculation problem, most of you will die.
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
We will be sent in to clean up the fallout.
I like this article because it seems to go into decent depth on the “framework” that the author comes up with.
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.
The toilet.
If we were more connected to all the problems that exist in the world, we’d become acutely aware of just how much work there is to do, and we’d eagerly reach for any tool that could help us do more, faster.
Okay, but let's say this happens, and in your utopian world everyone feels equally capable, judges their skills accurately, and gets along... what do people do? Assign things and use git? What if you keep wanting to work on any of these things and as soon as you are a week into every last thing you are working on, some random person comes along and says, hey dude (or dudette), I finished that, you were taking too long? What if that random person were an AI or chatbot that got bored?
'metaverse' aka the spatial internet (prolly by a new name).
Come on now: we translate vague ambitions into communications for non-living entities to do human bidding. Until we have recreated humanity as mythic gawds, there is a ton of work to do.
a professor of computer science at princeton comes up with slop like this. he supposed to be computing not a keynote of woo.
We'll be cleaning up tech debt from over-reliance on AI.
We can't do that until we clean up all the tech debt from promotion oriented development.