I've had quite a few conversations and read many thoughts on the subject of job security in the software industry through the years. New technologies, various crisis and crashes, just age, incoming "hordes" of less prepared developers, or whatever.
If I had to highlight the one thing all those conversations had in common it would be precisely this:
I thought that having this knowledge would set me apart
I think in the future, those who succeed will be equivalent to wayfinders.
People who _can_ see the wood for the trees, and are able to understand multiple (sometimes conflicting) requirements and work out a way through that solves the problems that arise, for all involved parties.
An understanding of domain, the ability to communicate effectively and a mind that can think laterally, will all be vital.
Past, Present, and Future. If you control the means of production you win. Knowledge, skill, and experience are largely irrelevant to the conversation. I’ve held this opinion for quite some time and would be interested to hear alternative perspectives.
> Past, Present, and Future. If you control the means of production you win.
Yeah, but we were talking about only success, not winning.
In the past and the present, you could succeed purely on a combination of skill, talent and labour. This approach looks like it will not work much longer.
We exchange our knowledge, time, and skill for money. If this exchange is no longer viable — because similar value can be accessed via LLM agents — we'll have no way of making money.
I do think some (non-billionaire) people will survive the transition, but the question then becomes: what happens to everyone else?
I don't think history bears this out. If you look at the most successful entrepreneurs of the computer age, none of them started out as owners of capital. Bill Gates, Jeff Bezos, Steve Jobs: yes, they had some level of privilege and opportunity, but they didn't start out as billionaires. Their success came from their ideas.
Gates famously came from a rich family, but Bezos did too - he used hundreds of thousands of dollars in investments from his immediate family members to get Amazon off the ground. Maybe 1 to 2% of Americans would be able draw that much from their family members if they were to launch a startup. If we define "bootstrapped" wealth as starting from an economic background within one standard deviation of the national average, then he doesn't count.
measuring programmer productivity is notoriously difficult. Does james, who shipped 20 features without testing thoroughly provide more value? or does joe, who patched a security hole in that time and avoided disaster? what about jason, who facilitated communication between them, and kept the infra going so their changes could go into prod without issues?
This also was true for teams, and indeed, businesses. It's not a property of the code itself, its a property of products and outcomes. I don't think AI agents doing the day to day changes will affect this directly (but people may have more time to think about these higher level problems, and increased volume of changes may make the issue more important)
I suppose, my best guess is that a team will be reduced to one or two people; the those that are left will be judged solely on outcomes.
Two (human) brains are always useful; the benefit of a human in these scenarios is that we can be accountable, and that we have a very real incentive to do well and not be fired. The LLM obviously doesn't care in that regard!
How do you do that in practice though? You won't know the engineer is a con-man until after you have spent $$ and months into the process. Then you are in the position of trusting nobody.
Knowledge depreciates, so it is clarifying to add time explicitly: I thought this knowledge would set me apart...
Forever? That seems over-optimistic for all occupations in all eras.
For the rest of my working career? This really hasn't been true in a long time either, especially in software, where technology changes on the order of years.
For the duration of my mortgage? The fondest hope, but pretty much like the above.
For the next 10 years? Here is the big change. Even for fields like medicine, where knowledge really did set you apart. The AI can adapt faster. AI is inside the human OODA loop.
The good news I think is that you have to be really really specialist for the specialist knowledge to actually be the important bit; for most it's the ability to obtain specialist knowledge, and apply it.
As long as we can adapt, move on to the next knowledge-needed area, we'll hopefully be alright.
(I think there are many analogies here to things people have always said about undergraduate study – e.g. it's about teaching you to learn, not teaching you the specific things you're taught, to be remembered and applied forever.)
May be for OO not yet for DA. Existential pressure drives better(fruitful) decisons and actions. AI has yet to incorporate that into training/inference.
does it never? seems to me that people pay me precisely for my knowledge, learned over many years. The knowledge translates into action, sure. But thats like the old parable about a plumber being paid €150 for a 5 minute consult that involves turning a single screw. "i could have turned that screw!" the customer cries, ignoring that yes, they could have. But they didn't know to.
I think perhaps the problem is instead "I thought that having this knowledge would set me apart, forever, without me having to learn anything else"
right. Apprentices will always grow, and so too must you, if you want to keep being paid. Their job is to come with new tools and new ideas, and your job is to keep a wider view into what you're doing and why, maintaining trust (you need to build the authority to tell apprentices no when their ideas might flood the customer's house), and keep moving towards other parts of the business and solving harder problems (working with sales, hiring, etc to manage customers and apprentices). AI will not build authority for you.
If your argument is that the customer themselves could use an AI or whatever to learn plumbing, that was always an option (libraries, google, youtube). They pay you so they don't have to worry about flooding their house (or at least have someone else to blame).
They might be able to "one shot" simple fixes that you might previously have assigned to an apprentice, but believe me, AIs are not about to start doing complex things for the layman that actually required seniors previously in either programming or plumbing, because very few of those things were just "type better into a computer". (build trust, speak confidently, know what doesn't work, take responsibility, test without breaking systems, communicate and work together with other professionals, have opinions)
I agree that it is easier than ever to start doing stuff, instead of reading. I don't think that means its easier to jump right to doing large projects. The problems to be solved there are often subtler, of a different class, and manifold, and a layman may not realise what has gone wrong until long afterwards or never (this also happened before, many people took on projects they weren't ready for and reinvented the wheel trying to solve issues they ran into)
it's oft debated, but I do fall on the side of "you should still know maths even in the age of the calculator/matlab/llms". I have found productive employment, and indeed tickets to speak to the big boys in their gilded palaces many times because graphs and charts are their favorite toys and knowing maths got me there. They have always been able to make things with excel, with matlab etc. Often they actually can make charts themselves, but they don't care to become experts in what data is important and what isn't.
The LLM isn't yet good enough to tell you what data matters. People act like LLMs are magical gods that do everything, but it is but another tool. It has limitations, just as it has strengths. It is not ultimately convincing, it is not infallible, and experts will keep finding edge cases all the damn time. Anyone working with them every day knows this, and you need to know it too.
I think a more sane minded customer would not mind paying for the assurance and having someone to blame in case things go wrong, not necessarily because of their domain knowledge.
I could theoretically learn everything about plumbing but would still rather call a professional for the peace of mind that it was done "correctly" and it the process goes wrong, I would have an instant fix instead of trying to go back and educating myself on plumbing more.
Could you consider that as part of knowledge? Yeah and also no. Because the knowledge can be copied and put into a LLM but legally a LLM cannot sign off on things like NDAs or take accountability like a human has to in these roles.
I agree. I also think that deciding that LLMs encode all knowledge perfectly, either now or in an imagined future, is foolish. My experience is that they match the average general state of experts among the field. The sort of thing a junior might read to start to grasp the general ideas and issues in a field. They rarely have opinions, or good intuitions around more specific scenarios. This is why the current equilibrium of a senior piloting one works so well- theyre leaning on it to speed up, but pushing it away from the "average" where circumstances demand.
We can argue about imagined future progress, but I don't see that getting much better, given that the literature doesn't often do that, and how often experts in one scenario end up being poorly suited given another set of facts.
Agreed. The ability to learn new things, and what characteristics their ability to learn has -- that's one dimension that strongly differentiates people in nearly any domain.
But there are other dimensions as well that differentiate people and determine their value to business, like the ability to be handed problems no one else can solve and stick with them through sheer stubbornness until solutions begin to emerge.
I don't know (also english is not my first language), but to me it takes knowledge to know what is the right tool for the job. To know what is required to make the client happy. To know where great code matters and where quick and dirty or nowdays vibe code is sufficient.
And that knowledge can be complex. It usually requires knowing how people think and act, who don't know how to open a terminal. Because those are the main people using software.
My concern is less about knowledge and more about the ability to communicate and make good decisions. I'm not sure how well it holds up against technology that can sometimes make a good showing at it, but is most importantly automated, cheap and subservient.
"Oh, we'll just ship production to China, and do the design and marketing in US, this is where the real value is anyway, China will never be able to do design and marketing as well as we do".
Literally same thing:
"Oh, we'll just let LLMs code, and we'll just do Taste. LLMs will never be able to do Taste"
Knowledge often does not produce competence, especially in the applicable market. I work on the system administration side of things, and I have encountered many output-competent developers that were immeasurably stupid, but very little incompetent ones with tons of cryptic knowledge and intuitive understanding of the systems they worked on.
It seems to me that knowledge doesn't always imply competence, but the lack of knowledge often very well explains incompetence. And, since the LLM is replacing the competence part without imprinting any knowledge on the one that wields it, it generates a lot of competent imbeciles that pass interviews and appear as though they not only do things, but know things as well. And once you reach that critical mass, sheeeeesh
>>I thought that having this knowledge would set me apart
The whole leetcode movement was designed to sell this idea that knowing a solution that can be looked up in a matter of minutes on the internet some how puts you astronomically ahead of those who don't. Strangely enough go look at that site itself and thousands submit working solutions to those problems.
Knowing a solution discovered by somebody the first time, is no test of capacity or ability to get work done. It would probably matter if you discovered solution to a novel problem by yourself. How does knowing the end result of a long process by other people decide your ability to do anything at all?
During interviews I have seen companies go to absurd lengths to justify these tests. Including asking candidates to imagine they might not have internet and might need to know these solutions.
The only skill that really matters in our line of work is today most popularly known as high agency lifestyle. And delivery skills largely depend on ownership. In my decades of experience with software work, not knowing a thing isn't even a correlating factor in getting things done.
Everyone but insane people like me want some kind of durable stability to their life
they don’t want to be forced to reinvent themselves every five years because the world is changing faster than it ever has
While I understand where people are coming from to an extent that’s just never been my lifestyle and so when I see people looking for some kind of long-term stability I just kind of baffled at what makes them think that that was ever possible.
It’s like the propaganda from the American 1950s nuclear family idealism really got locked in in a way that people believe that there was a real thing
And while it was certainly true that American baby boomers got to ride the economic pax Americana that happened from 1949 to today, that period is over
While it is still possible for you to have a career your career is most likely going to change every 5 to 10 years now and that’s just a fact of the society that we have built
we did not build society intentionally
It was built via attrition and the current leaders are the ones who are fully committed to monetary based global domination
Red Queen hypothesis is a hypothesis in evolutionary biology proposed in 1973, that species must constantly adapt, evolve, and proliferate in order to survive while pitted against ever-evolving opposing species.
Why do we always assume environments and other agents will always remain static.
AI maximalism is making a lot of assumptions that I think are not a given
* The curve of AI improvement will continue at the current pace
* AI companies will have the capital continue to expand infrastructure
* there will be some kind of functioning economy if all knowledge workers are replaced
There are strong headwinds to all three of these.
Hey it may come to pass but it’s very speculative at this point. I see a lot of tech people simply overlaying the progress curve of previous tech booms which is reductive.
Price of the current frontier may vary, but price for a given level of capability tends to drop pretty fast.
April of last year you'd get 1431 ELO[0] from o3-2025-04-16 for $8.00 per million output tokens. April of this year you can get 1436 ELO from deepseek-v4-flash for $0.2 per million output tokens.
Sure, but i don't think it's reasonable to hold given level of capability constant in a landscape where a give consumer of AI also has competitive pressures.
I can't use last year's SOTA model when my competitors can use the current SOTA model.
This is also baked in the eye watering valuations of model companies.
> I can't use last year's SOTA model when my competitors can use the current SOTA model.
Lots of people can. Tools don't need to be top of the line to be useful. Snap-on may exist, but they don't put Harbor Freight out of business.
Advanced IDEs exist but complex projects were still built in vim.
The more capable the budget models get, the lower the marginal gains from using the frontier models, even if the frontier models always stay 6 months ahead.
The technology already exists now on the algorithmic front for the next 10x drop between everyone adopting DeepSeek's MLA, MoE (mostly already done), Medusa (a better version of Google's speculative decoding), Kimi's Attn Residuals, and Mimo's Sliding Window Attn, and (possibly) Microsoft's 1.58b (this may be a nothing burger).
Historically, algorithmic gains are only ~30% of the pie, but there's enough out there to get to 10x, with just what's available already. The other ~70% of the pie is better training data (often synthetic) and distilling frontier knowledge. There's no sign we are tapped out on that front.
MoE isn’t the magical improvement you think it is. Logprobs of MoE models are always worse in quality than the dense equivalent and they struggler harder at very long context quality than equivalent dense models. This is why Chinese companies like qwen are releasing dense and MoE versions of their models at near equivalent sizes. I always use/prefer the dense one.
Speculative decoding usually only improves decode and sometimes actually harm prefill and for agentic coding prefill matters more.
You’re right about the rest but I need to set the record straight on these details.
AI/LLMs have been dramatically improving for 7+ years. There's now a lot more funding to support continued improvement. You're correct this is an "assumption", but continued improvement at the same pace (or faster) for the next 3+ years is just extrapolating a trend. Believing we've hit the top today is based on nothing at all. Continued improvement is much more likely.
You can only tell which part of the S-Curve you're on in retrospect. It's not something you can tell while you're experiencing it. Both scenarios of AI maxing out or continuing to improve are both likely.
That is not true. You can tell you are on the latter part of the S-Curve you are on, if the rate of change of capabilities has decreased compared to before. That is not what we are seeing right now. The rate of change is increasing, or is at best, stable.
Others have commented on the rate of AI improvement. It doesn't need to be current rate for it to be an even more serious problem in the very near future. That's irrespective of prior booms.
Regarding AI companies having capital to expand infrastructure; this is largely irrelevant. The cat is out of the bag, and you can already make serious gains by finetuning to local problems on a desktop machine. There is enough hardware out there to run these things en masse; it's more a question of power. Regardless, this stuff will always keep progressing, regardless of who is doing it.
Regarding the economy, it may be largely irrelevant if we, the people, don't do something very soon. The wheel keeps spinning as long as there are productive workers; it's just that those workers are being replaced by machines. The last year has increasingly demonstrated that you don't need normal people to buy your stuff to remain afloat. You can just keep selling amongst your rich friends while the masses starve, as long as _something_ is still producing what the wealthy want, and enough systems are in place to protect them.
> The curve of AI improvement will continue at the current pace
I guess this is trivially true if you say "maximalism" (hell, the maximalists think it will speed up as the AI becomes a super-AI-researcher), but as long as the rate of change is positive and not miniscule, it's hard to predict what 2035 looks like in software development.
These things are very hard to quantify, but making the progress that happened from Jan 2025-December 2025 repeat twice in 10 years would be enough for me to say I couldn't predict the day-to-day of a software engineer in 2035.
This is probably one of the more level headed takes in the comment thread. There's been a concerted marketing push to frame AI maximalism as an inevitability. More or less a "it's going happen anyways so let's go all in".
It's hardly an inevitability though (nothing is... and analogues to the industrial revolution are iffy at best, we haven't ever had an attempted replacement for intelligence itself before).
Society is doing this at an unprecedented cost and it's clear a large portion of the population is uneasy with it. Whether society in the US, Europe, and Asia will continue to allow such investment at the expense of everything else remains to be seen.
> Work that introduces new methods, highly creative ideas, or solutions that have not been used or experienced before. More generally, an approach that introduces an innovative strategy to solve a complex problem.
Something that I've been thinking about for the past year or so is coming to grips with the fact that the vast majority (anecdote) of software engineering work is not novel (and maybe that's okay). Few opportunities lend themselves to doing truly novel work. Other than infrastructure work and highly specialized software, pause and ask yourself when you last encountered software were you said "how the hell did they do that?" or "damn, that's nice" (for me, the most recent was Ghostty). I think much of the angst that people have when they fear for their job is coming to the realization that LLMs can do most of the "standard" work that a lot of highly compensated individuals currently do. We've built livelihoods around this and the threat of that coming to an end is genuinely frightening.
> I think much of the angst that people have when they fear for their job is coming to the realization that LLMs can do most of the "standard" work that a lot of highly compensated individuals currently do.
Amd do it better in most cases imo. Which is also hard to come to terms with, because there is a good bit of elitism/entitlement going around. The idea that a SWE is working at a higher level, which is beyond the reach of mere mortals, so therefore the high compensation is justified. Meanwhile everyone is, for the most part, doing some slight variation of the same thing as you suggested.
After starting out working minimum wage jobs I've always thought that the work gets easier and easier from there. Compensation and hard work are negativity correlated.
This is spot on ! Most of the work we really do is pure boilerplate and should be automated. While there are instances of interesting work those are far and few in between . The most recent instance of "how the hell did they do that?" for me was duckdb.
> Something that I've been thinking about for the past year or so is coming to grips with the fact that the vast majority (anecdote) of software engineering work is not novel (and maybe that's okay)
Correction, essentially 0% of software is novel. Git wasn't novel. Chromium wasn't novel. Linux wasn't novel. Even C when it came out wasn't novel. Likewise Unix. They're all permutations of either prior knowledge, or evolutions of already existing concepts. They only might _appear_ novel to people who lack the depth to see what technology really is. Effectively applied physics (which has been solved for... over a few centuries at this point?) which itself is applied mathematics. There is novely to be found in physics and math themselves, but it's far out of scope of practical engineering.
> pause and ask yourself when you last encountered software were you said "how the hell did they do that?"
Like every month for the past 5 years? The progress in machine learning is dizzying. It is astonishing what can be done now with text, images, audio, video, code, etc...
If you don't study it, however, you have no idea how it works or how to do it yourself.
Just kudos to OP for coming back. One thing I almost "hate" is that nowadays everyone can put something out there... videos, articles, etc., but when confronted with questions, you never see the discussion continue. YT videos are an example... SO MANY VIDEOS... People genuinely asking some good questions... and radio silence.
In my social network, there are two people impacted by LLMs. One was a security operations manager whose company reduced headcount upon introduction of some new LLM powered security tools. The other was UX designer. Both have been unemployed for 6+ months, and neither are likely to land a job in their field. The government hasn't stepped in and provided them with Universal Basic Income, and I wonder what will happen when my career is similarly impacted? Luckily I'm on the verge of retirement and should be able to support myself. However I have other friends who tried to day trade their 401k instead of work, and although back in the workforce, no longer have a nest egg. What's going to happen to them when they're inevitably put to pasture by AI?
I strongly agree with the author replies. I cannot grasp the reasonment of those who underestimate the power of these tools and their growing potential.
We should remember that the outside world care about things that work, not about how good they are inside sadly.
The outside world doesn't even care that things work, they care that it looks like it works long enough. Investors don't care that it's snake oil, as long as they're not left holding the bag.
AI is really good at making things that look like they work.
Well yes. This has been the history of the web. Frontpage generated really crappy code but people still used it to create websites. They didn't care about code quality just how it looked.
My mom was generating web pages with dreamweaver 25 years ago. People used it sure, but people certainly did care about the quality because it produced unmaintainable code. If people truly didn’t care about the quality people would have stopped learning how to write html and CSS around 2005.
> people would have stopped learning how to write html and CSS around 2005.
They did. Now it's all JSX or htmx or some other favored template or DSL monstrosity. Most people do not write HTML or CSS, and haven't in decades. You're spot on.
This says nothing about quality, however. Quality of HTML/CSS is purely subjective. A website's presentation layer cannot meet any technical standard metric for quality in engineering or manufacturing such as durability, reliability, efficiency, or safety.
I’m not going define away blocks of HTML inside of php scripts as not writing HTML by hand, but if you want to do that then sure most people were never writing HTML and CSS by hand.
They were replaced by other WYSIWYG website editors like Wix and Squarespace. These replacements are evidence in favor of the original claim. The specific products are irrelevant.
This is a sentiment a highly skilled framework knitter could have shared. Investors don't care if those newfangled steam-powered knitting machines produce inferior textiles as long as people buy it.
Parallels to the industrial revolution are apparent. And this is disturbing.
I don’t know, I don’t think anyone really cares. I can’t unmute videos on Twitter/X on iOS, it’s been like that for over a year. I get a new disclosure that my data was leaked about every month. Palantir and possible Claude targeted a girl’s school for missile strikes. I still have to tell Claude what day or time it is right now sometimes, or it’ll give me medical advice for my dog and the dosing or some important number is 2-5x off. At my last job, at a YC company, I was explicitly told to stop working on vulnerabilities that let you do things like arbitrarily change a user’s email address through unprotected admin endpoints. Ten years ago I would’ve gotten a raise for this.
We’re in some weird stage of capitalism where everything is a grift and nobody really cares anymore.
> We’re in some weird stage of capitalism where everything is a grift and nobody really cares anymore.
I've felt this way for a long time now. There's no substance to anything anymore. The US economy feels like a more advanced Nigerian scam, where very few things that the US makes provides anything of actual value and substance. Americans just can't afford quality anymore. We decided we'd like to have significant amounts of garbage rather than fewer quality things. This change was likely due to revving the economy toward quarterly profit goals and GDP growth over everything else. Theoretically, prioritizing investments should have "trickled down" where companies could have more capital to invest in workers, R&Dand quality...but instead it all just got soaked up into executive pay and the stock market.
Its short termism. its the same throughout the west and beyond. The markets want returns on a one or two year period, not long term investment. Executive pay is almost always tied to short term profits and share prices.
Yeah, it's the perversion of capitalism known as publicly traded companies.
Once you start noticing private companies (like some restaurant chains) manage to both treat their employees better and serve their customers better than the publicly traded ones, it seems like a very consistent trend.
Having pursuit of endless growth to appease otherwise uninvolved shareholders might not be the best way to do "capitalism".
Someone who is trying to build a business they can sell when they retire, or that they might leave to their kids, thinks on a completely different time scale. Smaller businesses are also run more by personal judgement and relationships than by rules and procedures.
> We should remember that the outside world care about things that work, not about how good they are inside sadly.
How good something is inside is directly responsible for how well it works. Your customers might not care about the former, but they will care when your cuts to the former impact the latter (and they always do impact it, in the end).
Actually, the outside world is in a constant state of low-grade rage at how poorly software works these days. Slop code will only accelerate this trend.
For the most part, people don’t need a thousand new features; the investment class does. Nobody gets mad at Craigslist.
> Actually, the outside world is in a constant state of low-grade rage at how poorly software works these days.
The problem is... what can we practically do? When the village fish monger 200 years ago sold shoddy fish, you could go to him, give him a few whacks with his fish, and even if the fish monger didn't improve the quality of the fish he sold in response, you at least got some kind of feeling you got justice.
Nowadays? For most of the world, those responsible for the bad software aren't in the same village any more, for 95% of the world's population the USA is on an entirely different continent. Can't do anything to hold anyone accountable, with the exception of cancelling a 5$/month subscription LOL and yelling at some poor Filipino or Indian callcenter grunt. If you're among the lucky 5% that lives in the US, sure, you can file lawsuits if the problem is egregious enough, but that's expensive and consumer protection has been gutted. And doing a copy of a plumber's brother event? Might give you people treating you like jesus-come-to-earth but in the end you'll still face capital punishment for it, if you don't get taken out by the private security of the uber rich before you can even raise your gun.
Whatever the eventual solution to the problem you raise will end up being, it is certain it will not be pretty... bottled up rage is not good for any society.
I was just reading comments the other day where people who dragging a company because they apparently used AI for some low level copywriting stuff. No art assets, no code (so far as anyone knows), not actually writing copy but more like "is everything spelled right, does the copy structure flow, have all these points been addressed, etc." Not only that but the only reason anyone even knew is because the company was completely up front and transparent about what they used AI for and what they didn't.
There is a visceral hate in the artistic community toward AI that doesn't really make sense to me tbh.
I would imagine it is like transcribing, an industry I was in for a little bit when I was younger. I saw the same transition there and imagine it will be elsewhere. First it's a bunch of people saying "AI can't take our jobs, our jobs are thinking jobs." Then it's "Sure, you could use AI, but there's no real advantage to it because it makes so many mistakes."
But pretty soon after that it's "Why am I paying a transcriptionist $3/minute when I can just have the machine auto-transcribe it and then my admin assistant can just scan it for mistakes."
Even if there still IS a quality difference between great writers and AI product, "good enough" is good enough for most customers, especially if you have to pay professional rates to get better.
> There is a visceral hate in the artistic community toward AI that doesn't really make sense to me tbh.
Really? Have you seen how the CEOs marketed it and talked about people in that community? Artists hate it, because they listened to what AI community and leadership were openly saying.
The weirdest thing on this all is how people find the hate puzzling considering initial rhetoric coming from the industry itself. And current rhetoric for that matter.
Right? AI evangelists never seem to miss an opportunity to be clueless about this
"Why do you guys hate AI so much? All I did was tell you it's so great that it makes your skills worthless and how glad I am that I won't need people like you around in the future to make art and designs. What's wrong with that?"
What I noticed was that it was not just about money. It is not like people could live out of art last decades anyway. Artists actually know it better then anyone. But the disdain toward things artistic people value and like was noticeable. Even when one has bad economic news, surely it should be possible to say then without being gleeful arrogant jerk. Which is exactly what the message was.
It is just ... we insulted those people, told them they are worthless, when they want to talk about things they like doing we tell them they should use AI and then we act all puzzled they hate us. How could that happen.
There's a large amount of voices, both online and off, that are sneering. Between crabs in a bucket happy that software devs are being clawed down, and people happy thinking they no longer need us
I'm worn down by a cacophony of voices telling me I'm no longer wanted or needed. I'm very tired.
I think you can't tell the difference until the "art" shows details of something you know well -- a place you've been, out a hobby or sport you do.
I'm thinking of this awful slop "art" I saw on Wayfair yesterday. As a surfer, it's hilarious. That's not how you stand on a board. It's not even a board. And the wave is terrible-- nobody wants to surf shorebreak like that! https://www.wayfair.com/decor-pillows/pdp/design-art-4-hawai...
I guess it could be a useful signal-- if you meet someone and they have it up in their home, you know they don't surf.
More generally, I think anything AI produces that's dense with factual details is inherently trash.
You could replace every software engineer on the planet with a perfect LLM tomorrow and it would not lead to mass unemployment-triggered riots. If you're talking about software engineering specifically, you're not correct. If you're talking about all labor, you're talking about something unrelated to the article.
The job of software engineering is more or less literally to automate every other job. If there are no software engineers it's because everything is or has been automated. If AI isn't capable of that then there's still software engineering to do and your argument collapses.
> Take copywriting. It was a profession that took years to master and paid well. This changed slowly as more professionals joined the market, even after the demand spike driven by ecommerce and adtech. Now, LLMs have destroyed the job for the vast majority of professionals.
riots lead to hiring more police, so loyalty, prostitution, and sponsored eunuchships will be future career list. Those who are lucky can become a rent-a-pal.
>> The demand for software most certainly has an upper limit.
> No, it does not. There is no ceiling for complexity.
There's an upper limit on everything. Maybe there's no ceiling on incidental complexity for s/ware development, but there sure as shit a ceiling on the essential complexity.
There are certainly limits to complexity people are willing to pay for. So if you are looking to make a living in development the fact that anyone will soon be able to do the basics and customise it for themselves is going to be a problem for you. Not directly, but because you'll be competing for fewer and fewer more interesting jobs that pay less and less over time (as development increasingly becomes a commodity task like waiting tables and stacking shelves), with the rest of us (maybe not me, I've already been unhappy in tech for years as remote work isn't good for my mental health, so I might bail early and beat the rush for those cushy table waiting jobs!).
You're assuming the current ensemble of commonly used software stacks is the most optimal there is. This assumption is simply wrong. Even looking at something simple like the office suite you can probably find countless areas where improvements can be made.
Exactly and this is true of many things. Much of the world is not zero sum, otherwise we'd have fallen into the "malthusian trap" several productivity booms ago.
We have thought that a few times with earlier technologies - a smaller chip requires less local reduction of entropy than a room sized computer. This may keep going for a long time yet.
I agree, his takes should not be dismissed lightly. I'm not sure about "demand is fixed" though. I feel like software demand has been declared saturated at least a few times.
Exactly, if we look at what projects are on-going now, look at Startups, they are practically solving all the same thing and most of them will be dead soon, we need to finally reach the era where tools to "zeroshot" anything becomes widespread to create new problems, but even by then, we will have an oversupply of tech workers, many will have to convert to a different field, many will not want to be paid based on callcenter type of work which is prompt-as-much-as-you-can, understandably.
It's quite hard to predict what will happen, but in a few years, I bet the unemployment rate of tech workers will be really high, we can just look at how many jobs are currently already replaceable but the owner of it is just lagging in the implementation of automation, it's probably already the large majority of tech jobs.
"fixed" is definitely incorrect but there's probably a ceiling on how fast the demand can grow, just because other bottlenecks will take over at some point.
Agreed. The limitations of human context window and communication bandwidth restrict the complexity of large-scale software.
LLM will have an extremely large context window and extremely high communication bandwidth in the future. Therefore, even more complex large-scale software will emerge.
There’s not much articulation except some personal snippets about someone caught in the hype cycle of a product, that the hive mind is buzzing about deafeningly.
Tools/improvements have rarely been negative in such a massive way except rare instances, and even then society moved on and past those tools to bigger & better things.
How many people today seriously consider agriculture as a career prospect but almost all humans who lived in the last 2000 years worked as peasant labor on a farm. We are thriving in comparison to that period of time.
This is the technology that aims to replicate all of the human functionality. So, the aim is unprecedented. You might not be convinced that this aim is achievable (despite having the human brain that achieves it, unlike, say, superluminal travel), but, at least, you might be inclined to recognize that something potentially unprecedented is going on.
Just because a generation or two down the line is better off does’t mean a lot of lives aren’t effected negatively when industries are destroyed or moved.
I guess my point is it’s rarely the transformational technology people talk it up to be.
5 years ago absolutely everyone was talking about how blockchains & ledgers were going to solve all the problems of the world, and executives needed blockchain & ledgers in their products. Now, no one cares.
Not saying that happens in this case, but don’t believe the hype so easy. Even job losses in the context of a radically different policies by the current administration doesn’t get a second thought, nor does the fact we’re no longer in a low interest rate environment.
The article: it's different this time because X and Y.
You: you're saying "it's different this time."
I don't know. It looks like AI really rots people's brains. As if that they just shut down their minds when they see an anything AI-related. Imagine if this article were about anything else, like:
Article: the stock bubble is going to burst because...
Comment: your argument boils down to "the stock bubble is going to burst."
It'd be so stupid. But somehow when it comes to AI this kind of weird comment is tolerated even celebrated.
I agree with all of it, and I think author did a really good job at actually saying what's true, it's almost like developers don't want to hear it.
I feel that OP has reach that point because he went out of the basic tooling like Claude Code (at least in its default state) and embrace multi-model, automatic reviewing, fuse, loops and so-on, when it's done right, well, failure rate to solve issues is <1%, this is exactly why you arrive to that kind of depressing thoughts afterward and it's spot-on.
Many people will disagree because they are still at the vibe coding stage, not "as much as I can prompt will be automatically done stage". Claude Code imo is deliberately not implementing the best ways for users to work, they have recently implemented Workflows but that's almost a year late, many companies are doing this since always and that's just part of basic tooling nowadays.
People talk about models and benchmarks score while genuinely I'm baffled because they seem to ignore that that same benchmark can reach 99% by levering tooling intelligently, we don't really need better models (at least for coding), we just need adoption of proper methods. The day developers will discover that they are already able to solve 300 issues in a single day with ZERO supervision in complex Rust codebases, I'm sure they'll change their mind.
Our bottleneck in our team is currently just having the mental bandwidth to type as much as possible, it's kinda sad, it is becoming all absurd.
If you are still watching the output of the model for coding tasks, I bet you haven't challenged your own methodologies, yet.
"There's this talk about Jevons Paradox but I disagree."
In my position, our team is clearly displaying "increased demand due to increased efficiency". I admit our position may be situational -- but my anecdote seems more substantive and speculative than "I disagree" from my vantage at least.
Every freelancer that switched to AI feels exactly what happened even if they can't name it.
We became for AI what our clients were for us. Some hate it, some love it.
To feel safe in life our clients needed to have an actual business. Now when we are the clients of our AI we are scared, because now we need to have an actual viable business. Economic machine that works. Because the old model of just selling our time and effort to a client no longer works, when we are the clients.
I think people are far too dismissive of just how well-suited programming is to the exact form of LLMs.
Extremely formal syntax, limited ambiguity, simple verifiable testing procedures, and colossal well-documented training sets.
I don't yet buy that the successes of coding agents will apply nearly as well to other professions. "Correct more often than not when asked a random accounting question" really isn't any indication to me that they'll get there.
> If the models (and harnesses) keep getting better at the same pace for the foreseeable years, we are heading to a world where the profession is commoditized to the ground. There's this talk about Jevons Paradox but I disagree. The demand for software most certainly has an upper limit.
This entire section is backwards to me.
The current state of a lot of different domains I've been in is that they tend to center around 2-3 major, generic products that all get retrofitted to fit those smaller/medium-sized businesses. Now that the economics have shifted, it makes sense for those businesses to bring on software devs to build software tailored to their problem specifically.
And you can't compare copyrighting. It's a totally different field, with different goals and different time tables.
"I'm finding LLMs also competent at explaining and giving advice on other domain stuff I'm totally new to, which I have cross-checked with Legal/Product Managers and is usually right."
"Usually" is the keyword. Until it becomes "always" (counterintuitive for heuristic systems) or "almost always" some human experts will (/may?) be needed to babysit.
P.S. "_are_ usually right" since they are "LLMs". Methinks running the response through an LLM could've made it more "right".
>Agents used to be bad at this kind of stuff in my workplace as well, but newer models + agent-friendly documentation + AGENT.md begging agents to read the fucking docs before coding changed this landscape for us here.
Wouldn't that be true for humans as well? If you have documentation explaining a rule and you read it, you may not need to reach out to coworkers.
Otherwise I think the author's concerns are 100% valid.
> > This anonymous article is likely more FUD from the AI industry. "Just give up,you can't beat the machine. Please go quietly, we want to take your place and it's easier for everybody if you don't resist because you believe it's pointless"
> > So blog with single post hyping LLMs. Oh and the domain name "human-in-the-loop". Call me suspicious.
> If after reading what I just said in the reply above you still think I'm an "AI shill" or "lab shill", there's nothing I can do for you.
Yes there isn’t. Because they look indistinguishable.
Replacement Inevitability with a human face, along with all the human concern; “I am part of it and it scares me.”
> Yeah, that's what I'm doing right now. I'm one of the engineers who's constantly committing to improve our agentic tooling, I use different models to do adversarial code reviews, I keep a toolbelt of skills and prompts, etc. I have effectively become the so-called "AI-native engineer" (gosh, I hate that term).
Some CEO gloating about replacing all-knowledge-work gets skepticism, eye-rolls and resentment. Someone in the trenches having human feelings about it generates both sympathetic and ecocentric fear.
---
And maybe autor intent does not matter? The original submission was massively “popular”. It served its purpose.
> This anonymous article is likely more FUD from the AI industry.
Literally today I got like 4 AI ads literally mocking "old people still using excel", trying shame and insecure people into some AI whatever product.
This is literally the first technology that is trying to scare and mock me into using it. All it actually does is that I am growing to hate it, honestly along with tech industry itself. Which I used to like.
I am having a similar sentiment change about our industry as well. The more AI's marketing plays purely on fear and shame, the more I want to see it fail. If Anthropic, OpenAI, and the other power players continue in this direction, I hope the graduation speech boos are just the start.
Tax I could do to some extend but I once (for laughs) had a go at scripting up Dutch work hour laws because no one could do it in their head. This was so terrifyingly complex that I'm convinced many laws should be rewritten to make it easier to code.
The problem looks something like (not a real example): Type Z hours maximum A per day, B per week, C per month, D per year. E more hours than A is allowed every F weeks but no more than G per month and H per year. More than B is allowed... etc Minimum rest hours I per day, J per week, K per two weeks, L per month. More is allowed every 7.5 days unless it is full moon and maximum hours per day were exceeded at least 3 times in the last 82 days except from solar eclipses or if the Kings is married 12.5 years or if the employee gave birth in the last 472 hours.
My employer has software to make the schedules. It cant tell where shifting around shifts is possible but you can try do it and it will tell you why it isn't possible.
I was hoping to calculate if multiple shifts can be shifted around to facilitate someones day off. Sometimes it just cant be made to work but if people are willing and there is a hole you end up doing it anyway. (I've done a triple shift once because the coworker wanted to bring his wife to the hospital.) Employees earn undocumented days off... and then you end up with multiple schedules, the real one and the official one. Possibly extra copies depending on who knows what is really going on. This cant be the way...
Better just have modern laws that make sense in code.
A part of the puzzle that rarely gets discussed is something that predated LLMs entirely-- "software engineering" and "programming" have been conflated for a long time now and there's a huge gamut of roles out there.
The practice of writing code, or programming, in recent years has really fallen into two buckets:
The vast majority of folks are given a task, they write code to complete that task, and the task completion then counts towards some objective (eg; a new feature, product or fixing a bug). Perjoratively, they've been known as "ticket takers".
A much smaller group have instead worked in the other direction-- identifying where improvements can be made to a product, piece of infrastructure, or pain point and transformed that into tasks that can then be solved via code.
How much of a role you play in that strategy and formulation has been the real differentiator. Not so much what you know. While these are correlated, they're very different.
At a high level, it's been the difference between "developer" and "engineer" but the reality is the titles have become somewhat meaningless in recent years where many "engineers" are just doing the same CRUD tasks over and over.
The reason this matters is that at some point, you can only abstract so far... the requirements for what to build have to come from somewhere. At the most extreme case, there's only the CEO and a company that's nothing but AI agents. In the least extreme case (today) each line worker could manage 1 or more LLMs/agents.
It's not entirely clear to me or frankly a large portion of those in the industry that we're suddenly on pace for one outcome vs another. But I do think that software isn't particularly unique here other than it was an initial starting point for LLMs to deliver value. All white collar work is at risk including CEOs.
And if that happens it would be outlandish to think a utopia emerges... the opposite is far more likely.
You are correct that your career is changing, but it's not like AI is going to go away.
In the 1990s when crypto went to court. It was determined that really anything coming from AI is protected speech. Very few exceptions, AI cant export a few things.
So you're never seeing AI go away, which means you need to transition/adapt.
> The models will learn good engineering principles at some point.
This is just silly. It's fairly clear that the current design (by which I mean the entire concept of the deep neural network) has its limits and that they just aren't that good. We're seeing lots of other AI and software engineering brought to bear, but there's nothing 'inevitable' that means this is close.
"at some point" is so vague as to be irrelevant. Fusion might be the dominant source of electricity "at some point". Equally, AI knowing good principles could be 30 years away.
Don't assume that hard intellectual challenges are solvable on faith. Look at what's currently possible.
> It's fairly clear that the current design (by which I mean the entire concept of the deep neural network) has its limits
Maybe, but people have been saying deep learning is about to hit a wall since 2012, and many reasonable-sounding "machines fundamentally can't do X" have since fallen.
Feels like we're standing on a roof with floodwater up to our ankles - maybe it stops rising now, but we didn't foresee it getting anywhere near this high in the first place.
I do agree that progress will probably be more slow/gradual than others seem to predict, no "hard takeoff", but even being decades away is still relevant to someone starting a career in software development.
Here is another scenario. You mobilize your local community or even country to choose option 1, communal ownership. Then another country or region follows path 2. If option 2 is more productive (maybe because you redirected productivity gains towards wellbeing instead of more compute) you are toast, you now have a sort of Cold War scenario where eventually the technofeudalists will have the upper hand and could outcompete or destroy the technocommunalists or whatever you want to call them.
Note that I am not shitting on the idea of option 1 at all, in fact personally I would very much like to see it succeed. I just think this is more of a global issue than a local one.
These thought scenarios are bunk. There is no isolated silo in the real world. See foreign interference between Capitalist and Communist countries. Cuba isn’t even allowed to be a sovereign, Communist country in the Carribean (see attempted invasions, embargoes, now the crippling oil embargoes).
> Note that I am not shitting on the idea of option 1 at all, in fact personally I would very much like to see it succeed. I just think this is more of a global issue than a local one.
That’s why socialists argue for international revolution.
I attribute the excitement of the VC and CEO cast to the same underlying motive, but I think there are at least several other ways all this could play out:
- the Cul-de-Sac: AI progress flattens as scaling data and compute, RL and algorithmic improvements hit diminishing returns.
- democratization: LLMs decentralize, mirroring the shift from mainframes to personal computers.
- AI creates new jobs and thus new dependencies for the capitalist class
> 1) communal ownership of the means of production, e.g. of compute
As every communist, you forget about economics of such a system. How would you prevent concentration of capital in this system? Planned economy? Planned by whom?
Some (less) food is produced on farms and kitchens.
It tastes good, and keeps you healthy.
I don't really care who/what wrote the code. I don't even really care about the code at all. What I care about is the end product.
The problem is not "code quality" the problem is that billionaire sociopaths have removed human judgement (and human morality) from the dev loop. This started long before AI.
Coders are hyperfocused on style and missing the substance. We are entering a world where rich bastards can produce evil software without any checks whatsoever.
At least when humans were required to write the code, they had to find and retain unscrupulous humans. Now they're completely unfettered, and we're soon going to learn the precise shape of the digital prisons they're constructing.
I don't entirely disagree, but as with many other posts on this topic…
> They will come for finance, biology, law, marketing, all knowledge work. That's their stated goal and they're already teasing it with "ChatGPT for Health" and similar launches. They're working on "harnesses" for other fields, it's just a matter of time before we have "Claude Finance Analyst" or something.
…
> Beg to disagree. The models will learn good engineering principles at some point.
…
> Stop and think, don't try to predict the future using (bad) past examples.
Don't try to prediction the future based on the past.
Also, here is my doomsday prediction.
Thats kind of ironic.
Heres a more thoughtful take: everything is an s curve.
Things start out fast, then they slow down.
It happens in learning, in tech, in literally everything.
The question (unanswered) is where we are in that curve.
If I had to highlight the one thing all those conversations had in common it would be precisely this:
And it never does.People who _can_ see the wood for the trees, and are able to understand multiple (sometimes conflicting) requirements and work out a way through that solves the problems that arise, for all involved parties.
An understanding of domain, the ability to communicate effectively and a mind that can think laterally, will all be vital.
In the future, those who succeed will be the owners of capital.
No. In the future, those who succeed will be the children of the owners of capital.
See The Economist, February 2025: https://archive.is/PCoWl
You can also inherit talent, but "the descendants of those worthy are worthy" is a belief humanity spilled a lot of blood to get away from.
Yeah, but we were talking about only success, not winning.
In the past and the present, you could succeed purely on a combination of skill, talent and labour. This approach looks like it will not work much longer.
We exchange our knowledge, time, and skill for money. If this exchange is no longer viable — because similar value can be accessed via LLM agents — we'll have no way of making money.
I do think some (non-billionaire) people will survive the transition, but the question then becomes: what happens to everyone else?
Something happened in the 80s, and it wasn't "the dawn of a new technology". It happened specifically in the US, and was done by their government.
The results will hopefully be a lot more tangible.
I suppose, my best guess is that a team will be reduced to one or two people; the those that are left will be judged solely on outcomes.
Two (human) brains are always useful; the benefit of a human in these scenarios is that we can be accountable, and that we have a very real incentive to do well and not be fired. The LLM obviously doesn't care in that regard!
Forever? That seems over-optimistic for all occupations in all eras.
For the rest of my working career? This really hasn't been true in a long time either, especially in software, where technology changes on the order of years.
For the duration of my mortgage? The fondest hope, but pretty much like the above.
For the next 10 years? Here is the big change. Even for fields like medicine, where knowledge really did set you apart. The AI can adapt faster. AI is inside the human OODA loop.
As long as we can adapt, move on to the next knowledge-needed area, we'll hopefully be alright.
(I think there are many analogies here to things people have always said about undergraduate study – e.g. it's about teaching you to learn, not teaching you the specific things you're taught, to be remembered and applied forever.)
I think perhaps the problem is instead "I thought that having this knowledge would set me apart, forever, without me having to learn anything else"
If your argument is that the customer themselves could use an AI or whatever to learn plumbing, that was always an option (libraries, google, youtube). They pay you so they don't have to worry about flooding their house (or at least have someone else to blame).
They might be able to "one shot" simple fixes that you might previously have assigned to an apprentice, but believe me, AIs are not about to start doing complex things for the layman that actually required seniors previously in either programming or plumbing, because very few of those things were just "type better into a computer". (build trust, speak confidently, know what doesn't work, take responsibility, test without breaking systems, communicate and work together with other professionals, have opinions)
it's oft debated, but I do fall on the side of "you should still know maths even in the age of the calculator/matlab/llms". I have found productive employment, and indeed tickets to speak to the big boys in their gilded palaces many times because graphs and charts are their favorite toys and knowing maths got me there. They have always been able to make things with excel, with matlab etc. Often they actually can make charts themselves, but they don't care to become experts in what data is important and what isn't.
The LLM isn't yet good enough to tell you what data matters. People act like LLMs are magical gods that do everything, but it is but another tool. It has limitations, just as it has strengths. It is not ultimately convincing, it is not infallible, and experts will keep finding edge cases all the damn time. Anyone working with them every day knows this, and you need to know it too.
I could theoretically learn everything about plumbing but would still rather call a professional for the peace of mind that it was done "correctly" and it the process goes wrong, I would have an instant fix instead of trying to go back and educating myself on plumbing more.
Could you consider that as part of knowledge? Yeah and also no. Because the knowledge can be copied and put into a LLM but legally a LLM cannot sign off on things like NDAs or take accountability like a human has to in these roles.
We can argue about imagined future progress, but I don't see that getting much better, given that the literature doesn't often do that, and how often experts in one scenario end up being poorly suited given another set of facts.
But there are other dimensions as well that differentiate people and determine their value to business, like the ability to be handed problems no one else can solve and stick with them through sheer stubbornness until solutions begin to emerge.
Not producing holy code in the academic best language.
"Oh, we'll just ship production to China, and do the design and marketing in US, this is where the real value is anyway, China will never be able to do design and marketing as well as we do".
Literally same thing:
"Oh, we'll just let LLMs code, and we'll just do Taste. LLMs will never be able to do Taste"
Except China is just humans in a different location so it shouldn't be surprising they can do things humans in the US can do.
LLMs are a totally distinct type of thing. It's possible they'll be able to do Taste but it's also quite possible they'll never be able to.
It seems to me that knowledge doesn't always imply competence, but the lack of knowledge often very well explains incompetence. And, since the LLM is replacing the competence part without imprinting any knowledge on the one that wields it, it generates a lot of competent imbeciles that pass interviews and appear as though they not only do things, but know things as well. And once you reach that critical mass, sheeeeesh
The whole leetcode movement was designed to sell this idea that knowing a solution that can be looked up in a matter of minutes on the internet some how puts you astronomically ahead of those who don't. Strangely enough go look at that site itself and thousands submit working solutions to those problems.
Knowing a solution discovered by somebody the first time, is no test of capacity or ability to get work done. It would probably matter if you discovered solution to a novel problem by yourself. How does knowing the end result of a long process by other people decide your ability to do anything at all?
During interviews I have seen companies go to absurd lengths to justify these tests. Including asking candidates to imagine they might not have internet and might need to know these solutions.
The only skill that really matters in our line of work is today most popularly known as high agency lifestyle. And delivery skills largely depend on ownership. In my decades of experience with software work, not knowing a thing isn't even a correlating factor in getting things done.
they don’t want to be forced to reinvent themselves every five years because the world is changing faster than it ever has
While I understand where people are coming from to an extent that’s just never been my lifestyle and so when I see people looking for some kind of long-term stability I just kind of baffled at what makes them think that that was ever possible.
It’s like the propaganda from the American 1950s nuclear family idealism really got locked in in a way that people believe that there was a real thing
And while it was certainly true that American baby boomers got to ride the economic pax Americana that happened from 1949 to today, that period is over
While it is still possible for you to have a career your career is most likely going to change every 5 to 10 years now and that’s just a fact of the society that we have built
we did not build society intentionally
It was built via attrition and the current leaders are the ones who are fully committed to monetary based global domination
Why do we always assume environments and other agents will always remain static.
* The curve of AI improvement will continue at the current pace
* AI companies will have the capital continue to expand infrastructure
* there will be some kind of functioning economy if all knowledge workers are replaced
There are strong headwinds to all three of these.
Hey it may come to pass but it’s very speculative at this point. I see a lot of tech people simply overlaying the progress curve of previous tech booms which is reductive.
Frontier AI is already good enough to be very useful for engineering. It's too costly for many places where it could be useful today.
The cost for the same quality of output is going to drop at least 10x over the next 18-24 months.
And likely again in the following 18-24 months.
At the same time, the cost per watt is going to down ~25%, and at the same time speed will increase (also valuable since time is money).
How do you know that?
In 2026 the prices have been spiking. It now costs orders of magnitude more than it did in November.
April of last year you'd get 1431 ELO[0] from o3-2025-04-16 for $8.00 per million output tokens. April of this year you can get 1436 ELO from deepseek-v4-flash for $0.2 per million output tokens.
[0]: https://huggingface.co/spaces/lmarena-ai/arena-leaderboard
I can't use last year's SOTA model when my competitors can use the current SOTA model.
This is also baked in the eye watering valuations of model companies.
Lots of people can. Tools don't need to be top of the line to be useful. Snap-on may exist, but they don't put Harbor Freight out of business.
Advanced IDEs exist but complex projects were still built in vim.
The more capable the budget models get, the lower the marginal gains from using the frontier models, even if the frontier models always stay 6 months ahead.
You can use open source models of equivalent or better capabilities for ~90% less cost...
If you kick and scream hard enough, you can always find a data point to make sure you're correct.
No one is saying that the Opus model last year costs 90% less now than it does this year.
That's not how it works.
There are better, more efficient models with equivalent capabilities that are 90% cheaper (see DeepSeek v4 Pro).
Historic trends, every 18 months, performance for the same level of quality has gone down 90%.
See: https://www.reddit.com/r/LocalLLaMA/comments/1gpr2p4/llms_co...
And Chart 13 here: https://www.rdworldonline.com/ais-great-compression-20-chart...
And here: https://epoch.ai/data-insights/llm-inference-price-trends
The technology already exists now on the algorithmic front for the next 10x drop between everyone adopting DeepSeek's MLA, MoE (mostly already done), Medusa (a better version of Google's speculative decoding), Kimi's Attn Residuals, and Mimo's Sliding Window Attn, and (possibly) Microsoft's 1.58b (this may be a nothing burger).
Historically, algorithmic gains are only ~30% of the pie, but there's enough out there to get to 10x, with just what's available already. The other ~70% of the pie is better training data (often synthetic) and distilling frontier knowledge. There's no sign we are tapped out on that front.
> In 2026 the prices have been spiking.
That's not for the SAME level of output...
Speculative decoding usually only improves decode and sometimes actually harm prefill and for agentic coding prefill matters more.
You’re right about the rest but I need to set the record straight on these details.
Regarding AI companies having capital to expand infrastructure; this is largely irrelevant. The cat is out of the bag, and you can already make serious gains by finetuning to local problems on a desktop machine. There is enough hardware out there to run these things en masse; it's more a question of power. Regardless, this stuff will always keep progressing, regardless of who is doing it.
Regarding the economy, it may be largely irrelevant if we, the people, don't do something very soon. The wheel keeps spinning as long as there are productive workers; it's just that those workers are being replaced by machines. The last year has increasingly demonstrated that you don't need normal people to buy your stuff to remain afloat. You can just keep selling amongst your rich friends while the masses starve, as long as _something_ is still producing what the wealthy want, and enough systems are in place to protect them.
I guess this is trivially true if you say "maximalism" (hell, the maximalists think it will speed up as the AI becomes a super-AI-researcher), but as long as the rate of change is positive and not miniscule, it's hard to predict what 2035 looks like in software development.
These things are very hard to quantify, but making the progress that happened from Jan 2025-December 2025 repeat twice in 10 years would be enough for me to say I couldn't predict the day-to-day of a software engineer in 2035.
It's hardly an inevitability though (nothing is... and analogues to the industrial revolution are iffy at best, we haven't ever had an attempted replacement for intelligence itself before).
Society is doing this at an unprecedented cost and it's clear a large portion of the population is uneasy with it. Whether society in the US, Europe, and Asia will continue to allow such investment at the expense of everything else remains to be seen.
> Work that introduces new methods, highly creative ideas, or solutions that have not been used or experienced before. More generally, an approach that introduces an innovative strategy to solve a complex problem.
Something that I've been thinking about for the past year or so is coming to grips with the fact that the vast majority (anecdote) of software engineering work is not novel (and maybe that's okay). Few opportunities lend themselves to doing truly novel work. Other than infrastructure work and highly specialized software, pause and ask yourself when you last encountered software were you said "how the hell did they do that?" or "damn, that's nice" (for me, the most recent was Ghostty). I think much of the angst that people have when they fear for their job is coming to the realization that LLMs can do most of the "standard" work that a lot of highly compensated individuals currently do. We've built livelihoods around this and the threat of that coming to an end is genuinely frightening.
Amd do it better in most cases imo. Which is also hard to come to terms with, because there is a good bit of elitism/entitlement going around. The idea that a SWE is working at a higher level, which is beyond the reach of mere mortals, so therefore the high compensation is justified. Meanwhile everyone is, for the most part, doing some slight variation of the same thing as you suggested.
After starting out working minimum wage jobs I've always thought that the work gets easier and easier from there. Compensation and hard work are negativity correlated.
Correction, essentially 0% of software is novel. Git wasn't novel. Chromium wasn't novel. Linux wasn't novel. Even C when it came out wasn't novel. Likewise Unix. They're all permutations of either prior knowledge, or evolutions of already existing concepts. They only might _appear_ novel to people who lack the depth to see what technology really is. Effectively applied physics (which has been solved for... over a few centuries at this point?) which itself is applied mathematics. There is novely to be found in physics and math themselves, but it's far out of scope of practical engineering.
Like every month for the past 5 years? The progress in machine learning is dizzying. It is astonishing what can be done now with text, images, audio, video, code, etc...
If you don't study it, however, you have no idea how it works or how to do it yourself.
oblig. xkcd https://xkcd.com/1425/
AI is really good at making things that look like they work.
This is a steelman of your argument.
it's look like clean and polished but its full of mess, and duplicate code, no conventions..
we're generating code faster but at what price. but the real and deep project intelligence still a bottleneck.
They did. Now it's all JSX or htmx or some other favored template or DSL monstrosity. Most people do not write HTML or CSS, and haven't in decades. You're spot on.
This says nothing about quality, however. Quality of HTML/CSS is purely subjective. A website's presentation layer cannot meet any technical standard metric for quality in engineering or manufacturing such as durability, reliability, efficiency, or safety.
But where are Frontpage and Dreamweaver now ?
Parallels to the industrial revolution are apparent. And this is disturbing.
Until they go wrong because they are not good inside.
We’re in some weird stage of capitalism where everything is a grift and nobody really cares anymore.
I've felt this way for a long time now. There's no substance to anything anymore. The US economy feels like a more advanced Nigerian scam, where very few things that the US makes provides anything of actual value and substance. Americans just can't afford quality anymore. We decided we'd like to have significant amounts of garbage rather than fewer quality things. This change was likely due to revving the economy toward quarterly profit goals and GDP growth over everything else. Theoretically, prioritizing investments should have "trickled down" where companies could have more capital to invest in workers, R&Dand quality...but instead it all just got soaked up into executive pay and the stock market.
Once you start noticing private companies (like some restaurant chains) manage to both treat their employees better and serve their customers better than the publicly traded ones, it seems like a very consistent trend.
Having pursuit of endless growth to appease otherwise uninvolved shareholders might not be the best way to do "capitalism".
How good something is inside is directly responsible for how well it works. Your customers might not care about the former, but they will care when your cuts to the former impact the latter (and they always do impact it, in the end).
For the most part, people don’t need a thousand new features; the investment class does. Nobody gets mad at Craigslist.
The problem is... what can we practically do? When the village fish monger 200 years ago sold shoddy fish, you could go to him, give him a few whacks with his fish, and even if the fish monger didn't improve the quality of the fish he sold in response, you at least got some kind of feeling you got justice.
Nowadays? For most of the world, those responsible for the bad software aren't in the same village any more, for 95% of the world's population the USA is on an entirely different continent. Can't do anything to hold anyone accountable, with the exception of cancelling a 5$/month subscription LOL and yelling at some poor Filipino or Indian callcenter grunt. If you're among the lucky 5% that lives in the US, sure, you can file lawsuits if the problem is egregious enough, but that's expensive and consumer protection has been gutted. And doing a copy of a plumber's brother event? Might give you people treating you like jesus-come-to-earth but in the end you'll still face capital punishment for it, if you don't get taken out by the private security of the uber rich before you can even raise your gun.
Whatever the eventual solution to the problem you raise will end up being, it is certain it will not be pretty... bottled up rage is not good for any society.
I looked at some examples and couldn't tell the difference.
There is a visceral hate in the artistic community toward AI that doesn't really make sense to me tbh.
But pretty soon after that it's "Why am I paying a transcriptionist $3/minute when I can just have the machine auto-transcribe it and then my admin assistant can just scan it for mistakes."
Even if there still IS a quality difference between great writers and AI product, "good enough" is good enough for most customers, especially if you have to pay professional rates to get better.
Really? Have you seen how the CEOs marketed it and talked about people in that community? Artists hate it, because they listened to what AI community and leadership were openly saying.
The weirdest thing on this all is how people find the hate puzzling considering initial rhetoric coming from the industry itself. And current rhetoric for that matter.
"Why do you guys hate AI so much? All I did was tell you it's so great that it makes your skills worthless and how glad I am that I won't need people like you around in the future to make art and designs. What's wrong with that?"
It is just ... we insulted those people, told them they are worthless, when they want to talk about things they like doing we tell them they should use AI and then we act all puzzled they hate us. How could that happen.
And you can see it again and again.
There's a large amount of voices, both online and off, that are sneering. Between crabs in a bucket happy that software devs are being clawed down, and people happy thinking they no longer need us
I'm worn down by a cacophony of voices telling me I'm no longer wanted or needed. I'm very tired.
I'm thinking of this awful slop "art" I saw on Wayfair yesterday. As a surfer, it's hilarious. That's not how you stand on a board. It's not even a board. And the wave is terrible-- nobody wants to surf shorebreak like that! https://www.wayfair.com/decor-pillows/pdp/design-art-4-hawai...
I guess it could be a useful signal-- if you meet someone and they have it up in their home, you know they don't surf.
More generally, I think anything AI produces that's dense with factual details is inherently trash.
Mass unemployment equals riots equals an end to the status quo.
I take it you haven't been listening to what the guys at the AI labs have been saying?
Plus that's what the whole article is about. I'm not sure how you could've missed that?
Even if code typing goes away, a new breed of engineering will take it's place.
> Take copywriting. It was a profession that took years to master and paid well. This changed slowly as more professionals joined the market, even after the demand spike driven by ecommerce and adtech. Now, LLMs have destroyed the job for the vast majority of professionals.
No, it does not. There is no ceiling for complexity.
> No, it does not. There is no ceiling for complexity.
There's an upper limit on everything. Maybe there's no ceiling on incidental complexity for s/ware development, but there sure as shit a ceiling on the essential complexity.
No ceiling.
There are perhaps limits to useful complexity.
There are certainly limits to complexity people are willing to pay for. So if you are looking to make a living in development the fact that anyone will soon be able to do the basics and customise it for themselves is going to be a problem for you. Not directly, but because you'll be competing for fewer and fewer more interesting jobs that pay less and less over time (as development increasingly becomes a commodity task like waiting tables and stacking shelves), with the rest of us (maybe not me, I've already been unhappy in tech for years as remote work isn't good for my mental health, so I might bail early and beat the rush for those cushy table waiting jobs!).
with abstractions and complexity there's essentially infinite demand for software
It's quite hard to predict what will happen, but in a few years, I bet the unemployment rate of tech workers will be really high, we can just look at how many jobs are currently already replaceable but the owner of it is just lagging in the implementation of automation, it's probably already the large majority of tech jobs.
It's never been declared saturated, with one exception in the six months following the dot-com crash.
I've been in the industry since the mid-90s. I have not seen automation with the potential to automate away everything for the average office worker.
LLM will have an extremely large context window and extremely high communication bandwidth in the future. Therefore, even more complex large-scale software will emerge.
Tools/improvements have rarely been negative in such a massive way except rare instances, and even then society moved on and past those tools to bigger & better things.
How many people today seriously consider agriculture as a career prospect but almost all humans who lived in the last 2000 years worked as peasant labor on a farm. We are thriving in comparison to that period of time.
5 years ago absolutely everyone was talking about how blockchains & ledgers were going to solve all the problems of the world, and executives needed blockchain & ledgers in their products. Now, no one cares.
Not saying that happens in this case, but don’t believe the hype so easy. Even job losses in the context of a radically different policies by the current administration doesn’t get a second thought, nor does the fact we’re no longer in a low interest rate environment.
You: you're saying "it's different this time."
I don't know. It looks like AI really rots people's brains. As if that they just shut down their minds when they see an anything AI-related. Imagine if this article were about anything else, like:
Article: the stock bubble is going to burst because...
Comment: your argument boils down to "the stock bubble is going to burst."
It'd be so stupid. But somehow when it comes to AI this kind of weird comment is tolerated even celebrated.
The argument boils down to: this is exactly the same as other times. And provides multiple examples.
I feel that OP has reach that point because he went out of the basic tooling like Claude Code (at least in its default state) and embrace multi-model, automatic reviewing, fuse, loops and so-on, when it's done right, well, failure rate to solve issues is <1%, this is exactly why you arrive to that kind of depressing thoughts afterward and it's spot-on.
Many people will disagree because they are still at the vibe coding stage, not "as much as I can prompt will be automatically done stage". Claude Code imo is deliberately not implementing the best ways for users to work, they have recently implemented Workflows but that's almost a year late, many companies are doing this since always and that's just part of basic tooling nowadays.
People talk about models and benchmarks score while genuinely I'm baffled because they seem to ignore that that same benchmark can reach 99% by levering tooling intelligently, we don't really need better models (at least for coding), we just need adoption of proper methods. The day developers will discover that they are already able to solve 300 issues in a single day with ZERO supervision in complex Rust codebases, I'm sure they'll change their mind.
Our bottleneck in our team is currently just having the mental bandwidth to type as much as possible, it's kinda sad, it is becoming all absurd.
If you are still watching the output of the model for coding tasks, I bet you haven't challenged your own methodologies, yet.
In my position, our team is clearly displaying "increased demand due to increased efficiency". I admit our position may be situational -- but my anecdote seems more substantive and speculative than "I disagree" from my vantage at least.
We became for AI what our clients were for us. Some hate it, some love it.
To feel safe in life our clients needed to have an actual business. Now when we are the clients of our AI we are scared, because now we need to have an actual viable business. Economic machine that works. Because the old model of just selling our time and effort to a client no longer works, when we are the clients.
Extremely formal syntax, limited ambiguity, simple verifiable testing procedures, and colossal well-documented training sets.
I don't yet buy that the successes of coding agents will apply nearly as well to other professions. "Correct more often than not when asked a random accounting question" really isn't any indication to me that they'll get there.
This entire section is backwards to me.
The current state of a lot of different domains I've been in is that they tend to center around 2-3 major, generic products that all get retrofitted to fit those smaller/medium-sized businesses. Now that the economics have shifted, it makes sense for those businesses to bring on software devs to build software tailored to their problem specifically.
And you can't compare copyrighting. It's a totally different field, with different goals and different time tables.
"Usually" is the keyword. Until it becomes "always" (counterintuitive for heuristic systems) or "almost always" some human experts will (/may?) be needed to babysit.
P.S. "_are_ usually right" since they are "LLMs". Methinks running the response through an LLM could've made it more "right".
"These AIs are usually right about things I don't know anything about" sounds like the textbook example of risky thinking though.
Wouldn't that be true for humans as well? If you have documentation explaining a rule and you read it, you may not need to reach out to coworkers.
Otherwise I think the author's concerns are 100% valid.
> > So blog with single post hyping LLMs. Oh and the domain name "human-in-the-loop". Call me suspicious.
> If after reading what I just said in the reply above you still think I'm an "AI shill" or "lab shill", there's nothing I can do for you.
Yes there isn’t. Because they look indistinguishable.
Replacement Inevitability with a human face, along with all the human concern; “I am part of it and it scares me.”
> Yeah, that's what I'm doing right now. I'm one of the engineers who's constantly committing to improve our agentic tooling, I use different models to do adversarial code reviews, I keep a toolbelt of skills and prompts, etc. I have effectively become the so-called "AI-native engineer" (gosh, I hate that term).
Some CEO gloating about replacing all-knowledge-work gets skepticism, eye-rolls and resentment. Someone in the trenches having human feelings about it generates both sympathetic and ecocentric fear.
---
And maybe autor intent does not matter? The original submission was massively “popular”. It served its purpose.
Literally today I got like 4 AI ads literally mocking "old people still using excel", trying shame and insecure people into some AI whatever product.
This is literally the first technology that is trying to scare and mock me into using it. All it actually does is that I am growing to hate it, honestly along with tech industry itself. Which I used to like.
The problem looks something like (not a real example): Type Z hours maximum A per day, B per week, C per month, D per year. E more hours than A is allowed every F weeks but no more than G per month and H per year. More than B is allowed... etc Minimum rest hours I per day, J per week, K per two weeks, L per month. More is allowed every 7.5 days unless it is full moon and maximum hours per day were exceeded at least 3 times in the last 82 days except from solar eclipses or if the Kings is married 12.5 years or if the employee gave birth in the last 472 hours.
My employer has software to make the schedules. It cant tell where shifting around shifts is possible but you can try do it and it will tell you why it isn't possible.
I was hoping to calculate if multiple shifts can be shifted around to facilitate someones day off. Sometimes it just cant be made to work but if people are willing and there is a hole you end up doing it anyway. (I've done a triple shift once because the coworker wanted to bring his wife to the hospital.) Employees earn undocumented days off... and then you end up with multiple schedules, the real one and the official one. Possibly extra copies depending on who knows what is really going on. This cant be the way...
Better just have modern laws that make sense in code.
The practice of writing code, or programming, in recent years has really fallen into two buckets:
The vast majority of folks are given a task, they write code to complete that task, and the task completion then counts towards some objective (eg; a new feature, product or fixing a bug). Perjoratively, they've been known as "ticket takers".
A much smaller group have instead worked in the other direction-- identifying where improvements can be made to a product, piece of infrastructure, or pain point and transformed that into tasks that can then be solved via code.
How much of a role you play in that strategy and formulation has been the real differentiator. Not so much what you know. While these are correlated, they're very different.
At a high level, it's been the difference between "developer" and "engineer" but the reality is the titles have become somewhat meaningless in recent years where many "engineers" are just doing the same CRUD tasks over and over.
The reason this matters is that at some point, you can only abstract so far... the requirements for what to build have to come from somewhere. At the most extreme case, there's only the CEO and a company that's nothing but AI agents. In the least extreme case (today) each line worker could manage 1 or more LLMs/agents.
It's not entirely clear to me or frankly a large portion of those in the industry that we're suddenly on pace for one outcome vs another. But I do think that software isn't particularly unique here other than it was an initial starting point for LLMs to deliver value. All white collar work is at risk including CEOs.
And if that happens it would be outlandish to think a utopia emerges... the opposite is far more likely.
In the 1990s when crypto went to court. It was determined that really anything coming from AI is protected speech. Very few exceptions, AI cant export a few things.
So you're never seeing AI go away, which means you need to transition/adapt.
TLDR: there will be less programmers and they will be better on average.
This is just silly. It's fairly clear that the current design (by which I mean the entire concept of the deep neural network) has its limits and that they just aren't that good. We're seeing lots of other AI and software engineering brought to bear, but there's nothing 'inevitable' that means this is close.
"at some point" is so vague as to be irrelevant. Fusion might be the dominant source of electricity "at some point". Equally, AI knowing good principles could be 30 years away.
Don't assume that hard intellectual challenges are solvable on faith. Look at what's currently possible.
AI has always been a field where https://imgs.xkcd.com/comics/tasks.png applies heavily.
Maybe, but people have been saying deep learning is about to hit a wall since 2012, and many reasonable-sounding "machines fundamentally can't do X" have since fallen.
Feels like we're standing on a roof with floodwater up to our ankles - maybe it stops rising now, but we didn't foresee it getting anywhere near this high in the first place.
I do agree that progress will probably be more slow/gradual than others seem to predict, no "hard takeoff", but even being decades away is still relevant to someone starting a career in software development.
This is a particularly ignorant thing to say.
(Also, both might be out of reach of the current AI architectures)
Note that I am not shitting on the idea of option 1 at all, in fact personally I would very much like to see it succeed. I just think this is more of a global issue than a local one.
> Note that I am not shitting on the idea of option 1 at all, in fact personally I would very much like to see it succeed. I just think this is more of a global issue than a local one.
That’s why socialists argue for international revolution.
That's why they're obsessed (to the point of psychosis) with "mastering" the new technique.
That's why they're all building a "harness".
What they don't realize is that the ironworker still ends up in chains.
The AI-enhanced become more and more AI-integrated and internally AI-fused and they don't even realize they eventually are not humans at all.
The non-AI underclass just hasn't got enough access to resources to survive long term and dies out with a whimper.
- the Cul-de-Sac: AI progress flattens as scaling data and compute, RL and algorithmic improvements hit diminishing returns.
- democratization: LLMs decentralize, mirroring the shift from mainframes to personal computers.
- AI creates new jobs and thus new dependencies for the capitalist class
- Any combination of the above.
As every communist, you forget about economics of such a system. How would you prevent concentration of capital in this system? Planned economy? Planned by whom?
Clearly you feel you've made yours, so what are you doing differently now to what you did before?
The capitalist class doesn't control Capital, Capital controls the capitalist class.
It tastes bad, and poisons you slowly.
Some (less) food is produced on farms and kitchens.
It tastes good, and keeps you healthy.
I don't really care who/what wrote the code. I don't even really care about the code at all. What I care about is the end product.
The problem is not "code quality" the problem is that billionaire sociopaths have removed human judgement (and human morality) from the dev loop. This started long before AI.
Coders are hyperfocused on style and missing the substance. We are entering a world where rich bastards can produce evil software without any checks whatsoever.
At least when humans were required to write the code, they had to find and retain unscrupulous humans. Now they're completely unfettered, and we're soon going to learn the precise shape of the digital prisons they're constructing.
> They will come for finance, biology, law, marketing, all knowledge work. That's their stated goal and they're already teasing it with "ChatGPT for Health" and similar launches. They're working on "harnesses" for other fields, it's just a matter of time before we have "Claude Finance Analyst" or something.
…
> Beg to disagree. The models will learn good engineering principles at some point.
…
> Stop and think, don't try to predict the future using (bad) past examples.
Don't try to prediction the future based on the past.
Also, here is my doomsday prediction.
Thats kind of ironic.
Heres a more thoughtful take: everything is an s curve.
Things start out fast, then they slow down.
It happens in learning, in tech, in literally everything.
The question (unanswered) is where we are in that curve.
Will they get better? Yes.
A lot better? A bit better? /shrug