I build automation tools for bookkeepers and accountants. The thing I keep seeing firsthand is that automation doesn't eliminate the job - it eliminates the boring part of the job, and then the job description shifts.
Before our tools: a bookkeeper spends 80% of their time on data entry and transaction categorisation, 20% on actually thinking about the numbers. After: those ratios flip. The bookkeeper is still there, still needed, but now they're doing the part that actually requires judgment.
The catch nobody talks about is the transition period. The people who were really good at the mechanical part (fast data entry, memorised category codes) suddenly find their competitive advantage has evaporated. And the people who were good at the thinking part but slow at data entry are suddenly the most valuable people in the room. That's a real disruption for real humans even if the total number of jobs stays roughly the same.
I think the "AI won't take your job" framing misses this nuance. It's not about headcount. It's about which specific skills get devalued and how quickly people can retool. In accounting at least, the answer is "slowly" because the profession moves at glacial speed.
I was with the author on everything except one point: increasing automation will not leave us with such abundance that we never have to work again. We have heard that lie for over a century. The stream engine didn't do it, electricity didn't do it, computers didn't do it, the Internet didn't do it, and AI won't either. The truth is that as input costs drop, sales prices drop and demand increases - just like the paradox they referred to. However, it also tends to come with a major shift in wealth since in the short term the owners of the machines are producing more with less. As it becomes more common place and prices change they lose much of that advantage, but the workers never get that.
> I was with the author on everything except one point: increasing automation will not leave us with such abundance that we never have to work again.
That's because we prefer improved living standards over less work. If we only had to live by the standards of one century ago or more, we could likely accomplish that by working very little.
What is interesting is the new things are cheap while the old stuff is now expensive. Average house in Australia is $1,000,000 while a TV is $500. The internet, social media, etc are cheap. Having someone repair your shoes is expensive.
What land prices? There's plenty of cheap land, it's just a bit far away from where most people live. But guess what, population densities were also lower a century ago.
Sure, just like less desirable products of every category cost less essentially by definition. But that’s not really a retort to someone asking by why land prices have risen so much.
As long as the owner class can leverage, "Hey, that {out group} is sitting around doing nothing and getting free money!" we'll never have anything close to UBI imo.
I still like the idea of clawing back mineral and water rights and paying for basic services out of the money payed by industry for the right to dirty our air and water. As a citizen you're entitled to compensation for the smoke you're breathing.
People talk about how socially progressive Scandinavia is but they have a shitload of petroleum resources and that money goes into social programs.
I'd love to make companies pay for their products' entire lifecycle, including disposal and cleanup. It's not right that a company can manufacture future-trash, sell it, and then absolve itself of the negative externality when the customer throws the product away and off it goes into a landfill.
If a company's process produces waste, it should bear the entire cost of leaving the environment the way they found it rather than just pumping the waste into it. If a company's products are not reused, it should bear the cost of taking the used product back and restoring the world to the way it was before the product was built.
There's been enormous pushback, pushes for privatizing (ruining) it, underfunding it from Congress, an absolute refusal to remove the criminally low income cap on contributions, etc.
You know. I have worked for almost two decades now, I can't afford to buy an apartment. People who have been useless their entire lives are getting government loans that they then pay off with welfare they get because they are doing nothing.
I'm not the ownership class, this is unfair. You are the ownership class. People with money or who grew up with money are overwhelmingly left leaning.
You can't afford an apartment because the ownership class is working very hard to keep housing prices high while paying you as little as possible for the two decades you have been working. Not because some disabled person elsewhere is struggling to get by on government loans and welfare.
You also need a system that is ok with giving you some of said abundance without you working.
Last year the US voted to hand over the reigns, in all branches of government, to a party whose philosophy is to slash government spending and reduce people’s dependence on the government.
To all the US futurists who are fantasizing about a post-scarcity world where we no longer work, I’d like to understand how that fits in with the current political climate.
It fits because now you can start up the conquering war machine and have a bunch of soldiers who're willing to kill in another country before starving in theirs
The thing a lot of people leave out is that literally billions must die for this to happen. In some fully automated world everyone except for a few tens of thousands of the owner class and their technicians will be unneeded. And then what to do?
>such abundance that we never have to work again. We have heard that lie for over a century.
I'm 0.6 centuries old and have never heard that said for existing tech. Human level AI could presumably do human work by definition but that's not the case before we get that, including now.
All of those technologies of the past can be managed by humans. Once computers can manage themselves AND other technologies and people, I think it'll be a different situation.
See, we have enough food to feed the entire world, every year.
It's not our production capabilities that keep people hungry; it's either greed or the problem of distribution.
Automation will definitely amplify production but it'll certainly continue to make rich richer and poor, well, the same. As inequality grows, so too does the authoritarian need to control the differential.
If you want to live with no electricity, no running water, and a lack of refrigerated food, you could do so purely on welfare. In that sense, we already have the UBI that Marx predicted.
However, most people want fruits and vegetables instead of getting rickets, goiter, and cholera from an 1800s diet. Many are even willing to work 80+ hours a week to do so.
Most non-banana republics across the world define the Minimum standard of living as having all of the things you listed, meaning welfare/social safety nets provide for that. As they should. We’re not animals.
Correct. Of course, that wasn't the case in 1750 or 1900. It wouldn't have been possible then.
Hence why prior technological changes that increased productivity didn't result in living lives of extended leisure, despite some predictions to that effect. Instead people kept working to raise the overall standard of living to what could be achieved when using the new tools to their fullest extent. Doing more, not doing the same with less effort. As you say, we're not animals. We can strive for better.
I think that is part of the point, though. As our productivity increases, we don’t see an increase in leisure, instead we see an increase in what we consider the minimum standard of living.
I appreciate that Finland considers Internet access of a minimum of 1 Mb to be a basic human right. I am not sure if other countries follow, but I wish the USA did.
So I can keep track of your wonderful comment, I'd like to add that looking up "banana republic", I realised Australia seems to fit that description perfectly! The latest crop they've come up with seems to be housing, but instead of fruit companies we have real estate cabals. With respect to the workers at the bottom of a banana republic, whats missing is the element of real choice. They say yes you can choose to not work harder but then you die early or suffer from disease, not much of a choice. Modern slavery is built on this idea of false choice.
I’m not really sure the point you’re trying to make behind “as long as you don’t mind dying early and painfully from easily preventable diseases technically you can live in utopia”. Would you mind clarifying your position here?
Whenever I get worried about this I comb through our ticket tracker and see that ~0% of them can be implemented by AI as it exists today. Once somebody cracks the memory problem and ships an agent that progressively understands the business and the codebase, then I'll start worrying. But context limitation is fundamental to the technology in its current form and the value of SWEs is to turn the bigger picture into a functioning product.
"The steamroller is still many inches away. I'll make a plan once it actually starts crushing my toes."
You are in danger. Unless you estimate the odds of a breakthrough at <5%, or you already have enough money to retire, or you expect that AI will usher in enough prosperity that your job will be irrelevant, it is straight-up irresponsible to forgo making a contingency plan.
My contingency plan is that if AI leaves me unable to get a job, we are all fucked and society as a whole will have to fix the situation and if it doesn’t, there is nothing I could have done about it anyway.
> You are in danger. Unless you estimate the odds of a breakthrough at <5%
It's not the odds of the breakthrough, but the timeline. A factory worker could have correctly seen that one day automation would replace him, and yet worked his entire career in that role.
There have been a ton of predictions about software engineers, radiologists, and some other roles getting replaced in months. Those predictions have clearly been not so great.
At this point the greater risk to my career seems to be the economy tanking, as that seems to be happening and ongoing. Unfortunately, switching careers can't save you from that.
I'm not worried about the danger of losing my job to an AI capable of performing it. I'm worried about the danger of losing my job because an executive wanted to be able to claim that AI has enhanced productivity to such a degree that they were able to eliminate redundancies with no regard for whether there was any truth to that statement or not.
It'd probably be cold day in Hell before AI replaces veterinary services, for example. Perhaps for mild conditions, but I cannot imagine an AI robot trying to restrain an animal.
> What's your contingency plan? Buy a subscription to the revolution?
I’ve been working on my contingency plan for a year-and-a-half now. I won’t get into what it is (nothing earth shattering) but if you haven’t been preparing, I think you’re either not paying enough attention or you’re seriously misreading where this is all going.
This ^ been a SWE for 20 years the market is the worst I have seen it, many good devs been looking for 1-2 years and not even getting a response, whereas 3-4 years ago they would have had multiple offers. Im still working but am secure in terms of money so will be ok not working (financially at least). But I expect a tsunami of layoffs this and next year, then you are competing with 1000x other devs and Indians who will works for 30% of your salary.
The memory problem is already being addressed in various ways - antigravity seems to keep a series of status/progress files describing what's been done, what needs doing, etc. A bit clunky, but it seems to work - I can open it up on a repo that I was working in a few days back and it seems to pick up this context such that I don't have to completely bring it up to speed every time like I used to have to do. I've heard that claude code has similar mechanisms.
I've been doing stuff with recent models (gemini 3, claude 4.5/6, even smaller, open models like GLM5 and Qwen3-coder-next) that was just unthinkable a few months back. Compiler stuff, including implementing optimizations, generating code to target a new, custom processor, etc. I can ask for a significant new optimization feature in our compiler before going to lunch and come back to find it implemented and tested. This is a compiler that targets a custom processor so there is also verilog code involved. We're having the AI make improvements on both the hardware and software sides - this is deep-in-the-weeds complex stuff and AI is starting to handle it with ease. There are getting to be fewer and fewer things in the ticket tracker that AI can't implement.
A few months ago I would've completely agreed with you, but the game is changing very rapidly now.
this works fine for like 2-3 small instruction sets. once you start getting to scale of a real enterprise system, the AI falls down and can't handle that amount of context. It will start ignoring critical pieces or not remember them. And without constant review AI will start priotizing things that are not your business priority.
I don't agree they have solved this problem, at all, or really in any way that's actually usable.
While true, my personal fear is that the higher-ups will overlook this fact and just assume that AI can do everything because of some cherry-pick simple examples, leading to one of those situations where a bunch of people get fired for no reason and then re-hired again after some time.
Exactly, now which one do you wanna be? The burned out ones but still working in SWE or the fired ones which in the long run converge to manual labor which AI can't do.
Not to mention in SWE case the salaries would be pushed down to match cost of AI doing it.
If you fail as a "higher up" you're no longer higher up. Then someone else can take your place. To the extent this does not naturally happen is evidence of petty or major corruptions within the system.
Just keep in mind that there are many highly motivated people directly working on this problem.
It's hard to predict how quickly it will be solved and by whom first, but this appears to be a software engineering problem solvable through effort and resources and time, not a fundamental physical law that must be circumvented like a physical sciences problem. Betting it won't be solved enough to have an impact on the work of today relatively quickly is betting against substantial resources and investment.
Why do you think it's not a physical sciences problem? It could be the case that current technologies simply cannot scale due to fundamental physical issues. It could even be a fundamental rule of intelligent life, that one cannot create intelligence that surpasses its own.
Plenty of things get substantial resources and investment and go nowhere.
Of course I could be totally wrong and it's solved in the next couple years, it's almost impossible to make these predictions either way. But I get the feeling people are underestimating what it takes to be truly intelligent, especially when efficiency is important.
That's not what I mean, rather than humans cannot create a type of intelligence that supersedes what is roughly capable from human intelligence, because doing so would require us to be smarter basically.
Not to say we can't create machines that far surpass our abilities on a single or small set of axis.
Seems like if evolution managed to create intelligence from slime I wouldn't bet on there being some fundamental limit that prevents us from making something smarter than us.
I'll believe that claim when a SOTA model can autonomously create content that matches the quality and length of any average PhD dissertation. As of right now, we're nowhere near that and don't know how we could possibly get there.
SOTA models are superhuman in a narrow sense, in that they have solid background knowledge of pretty much any subject they've been trained on. That's great. But no, it doesn't turn your AI datacenter into "a country of geniuses".
The implication of your assertion is pretty much a digital singularity. You’re implying that there will be no need for humans to interact with the digital world at all, because any work in the digital world will be achievable by AI.
Wonder what that means for meatspace.
Edit: Would also disagree this isn’t a physics problem. Pretty sure power required scales according to problem complexity. At a certain level of problem complexity we’re pretty much required to put enough carbon in the atmosphere to cook everyone to a crisp.
Edit 2: illustrative example, an Epic in Jira: “Design fusion reactor”
A lot of this can be provided or built up by better documentation in the codebase, or functional requirements that can also be created, reviewed, and then used for additional context. In our current codebase it's definitely an issue to get an AI "onboarded", but I've seen a lot less hand-holding needed in projects where you have the AI building from the beginning and leaving notes for itself to read later
Curious to hear if you've seen this work with 100k+ LoC codebases (i.e. what you could expect at a job). I've had some good experiences with high autonomy agents in smaller codebases and simpler systems but the coherency starts to fizzle out when the system gets complicated enough that thinking it through is the hard part as opposed to hammering out the code.
I'd estimate we're near a million LoC (will double check tomorrow, but wouldn't be surprised if it was over that to be honest). Huge monorepo, ~1500 engineers, all sorts of bespoke/custom tooling integrated, fullstack (including embedded code), a mix of languages (predominantly Java & JS/TS though).
In my case the AI is actively detrimental unless I hand hold it with every single file it should look into, lest it dive into weird ancient parts of the codebase that bear no relevance to the task at hand. Letting the latest and "greatest" agents loose is just a recipe for frustration and disaster despite lots of smart people trying their hardest to make these infernal tools be of any use at all. The best I've gotten out of it was some light Vue refactoring, but even then despite AGENTS.md, RULES.md and all the other voodoo people say you should do it's a crapshoot.
Ask the AI to figure out your code base (or self-contained portions of it, as applicable) and document its findings. Then correct and repeat. Over time, you end up with a scaffold in the form of internal documentation that will guide both humans and AIs in making more productive edits.
If you vector index your code base, agents can explore it without loading it into context. This is what Cursor and Roo and Kiro and probably others do. Claude Code uses string searches.
What helps is also getting it to generate a docs of your code so that it has map.
This is actually how humans understand a large code base too. We don’t hold a large code base in memory — we navigate it through docs and sampling bits of code.
cloc says ours is ~350k LoC and agents are able to implement whole features from well designed requirement docs. But we've been investing in making our code more AI friendly, and things like Devin creating and using DeepWiki helps a lot too.
Around 250k here. The AI does an excellent job finding its way around, fixing complex bugs (and doing it correctly), doing intensive refactors and implementing new features using existing patterns.
Our codebase is well over 250k and we have a hierarchy of notes for the modules so we read as much as we need for the job with a base memory that explains how the notes work
We have this in some of our projects too but I always wonder how long it's going to take until it just fails. Nobody reads all those memory files for accuracy. And knowing what kind of BS the AI spews regularly in day to day use I bet this simply doesn't scale.
Big tech might ahead of the rest of the economy in this experiment. Microsoft grew headcount by ~3% from June 2022 to June 2025 while revenue grew by >40%. This is admittedly weak anecdata but my subjective experience is their products seem to be crumbling (GitHub problems around the Azure migration for instance), and worse than they even were before. We'll see how they handle hiring over the next few years and if that reveals anything.
> ~0% of them can be implemented by AI as it exists today
I think it's more nuanced than that. I'd say that
- 0% can't be implemented by AI
- but a lot of them can be implemented much faster thanks to AI
- a lot of them can be implemented slower when using AI (because author has to fix hallucinations, revert changes that caused bugs)
As we learn to use these tools, even in their current state, they will increase productivity by some factor and reduce needs for programmers.
I look through the backlog for my team consisting of 9 trillion ill-defined (if defined at all) tickets that tells you basically nothing.
The large, overwhelming majority of my team's time is spent on combing through these tickets and making sense of them. Once we know what the ticket is even trying to say, we're usually out with the solution in a few days at most, so implementation isn't the bottleneck, nowhere near.
This scenario has been the same everywhere I've ever worked, at large, old institutions as well as fresh startups.
The day I'll start worrying is when the AI is capable of following the web of people involved to translate what the vaguely phrased ticket that's been backlogged for God knows how long actually means
I look at my ticket tracker and I see basically 100% of it that can be done by AI. Some with assistance because business logic is more complex/not well factored than it should be, but most of the work that is done AI is perfectly capable of doing with a well defined prompt.
Here's an example ticket that I'll probably work on next week:
Live stream validation results as they come in
The body doesn't give much other than the high-level motivation from the person who filed the ticket. In order to implement this, you need to have a lot of context, some of which can be discovered by grepping through the code base and some of which can't:
- What is the validation system and how does it work today?
- What sort of UX do we want? What are the specific deficiencies in the current UX that we're trying to fix?
- What prior art exists on the backend and frontend, and how much of that can/should be reused?
- Are there any scaling or load considerations that need to be accounted for?
I'll probably implement this as 2-3 PRs in a chain touching different parts of the codebase. GPT via Codex will write 80% of the code, and I'll cover the last 20% of polish. Throughout the process I'll prompt it in the right direction when it runs up against questions it can't answer, and check its assumptions about the right way to push this out. I'll make sure that the tests cover what we need them to and that the resultant UX feels good. I'll own the responsibility for covering load considerations and be on the line if anything falls over.
Does it look like software engineering from 3 years ago? Absolutely not. But it's software engineering all the same even if I'm not writing most of the code anymore.
This right here is my view on the future as well. Will the AI write the entire feature in one go? No. Will the AI be involved in writing a large proportion of the code that will be carefully studied and adjusted by a human before being used? Absolutely yes.
This cyborg process is exactly how we're using AI in our organisation as well. The human in the loop understands the full context of what the feature is and what we're trying to achieve.
But planning like this is absolutely something AI can do. In fact, this is exactly the kind of thing we start with on our team when it comes to using AI agents. We have a ticket with just a simple title that somebody threw in there, and we asked the AI to spin up a bunch of research agents to understand and plan and ask itself those questions.
Funny enough, all the questions that you posed are things that come up right away that the agent asks itself, and then goes and tries to understand and validate an answer, sometimes with input from the user. But I think this planning mechanism is really critical to being able to have an AI generate an understanding, then have it be validated by a human before beginning implementation.
And by planning I don't necessarily mean plan mode in your agent harness of choice. We use a custom /plan skill in Claude Code that orchestrates all of this using multiple agents, validation loops, and specific prompts to weed out ambiguities by asking clarifying questions using the ask user question tool.
This results in taking really fuzzy requirements and making them clear, and we automate all of this through linear but you could use your ticket tracker of choice.
Absolutely. Eventually the AI will just talk to the CEO / the board to get general direction, and everything will just fall out of that. The level of abstraction the agents can handle is on a steady upward trajectory.
I mean, what is the validation system? Either it exists in code, and thus can be discovered if you point the AI at repo, or... what, it doesn't exist?
For the UX, have it explore your existing repos and copy prior art from there and industry standards to come up with something workable.
Web scale issues can be inferred by the rest of the codebase. If your terraform repo has one RDS server, vs a fleet of them, multi-region, then the AI, just as well as a human, can figure out if it needs Google Spanner level engineering or not. (probably not)
Bigger picture though, what's the process of a human logs an under specified ticket and someone else picks it up and has no clue what to do with it? They're gonna go ask the person who logged the bug for their thoughts and some details beyond "hurr Durr something something validation". If we're at the point where AI is able to make a public blog post shaming the open source developer for not accepting a patch, throwing questions back to you in JIRA about the details of the streaming validation system is well within its capabilities, given the right set of tools.
Honestly curious, have you seen agents succeed at this sort of long-trajectory wide breadth task, or is it theoretical? Because I haven't seen them come close (and not for lack of trying)
Yeah I absolutely see it every day. I think it’s useful to separate the research/planning phase from the building/validadation/review phase.
Ticket trackers are perfect for this. Just start with asking AI to take this unclear, ambiguous ticket and come up with a real plan for how to accomplish it. Review the plan, update your ticket system with the plan, have coworkers review it if you want.
Then when ready, kick off a session for that first phase, first PR, or the whole thing if you want.
Opus 4.6, with all of the random tweaks I've picked up off of here, and twitter, is in the middle of rewriting my golang cli program for programmers into a swiftui Mac app that people can use, and it's totally managing to do it. Claude swarm mode with beads is OP.
As always, the limit is human bandwidth. But that's basically what AI-forward companies are doing now. I would be curious which tasks OP commenter has that couldn't be done by an agent (assuming they're a SWE)
This sounds bogus to me: if AI really could close 100% of your backlog with just a couple more humans in the loop, you’d hire a bunch of temps/contractors to do that, then declare the product done and lay off everybody. How come that isn’t happening?
Because there's an unlimited amount of work to do. This is the same reason you are not fired once completing a feature :-) The point of hiring a FTE is to continue to create work that provides business value. For your analogy, FTEs often do that by hiring temp, and you can think of the agent as the new temp in this case - the human drives an infinite amount of them
I think the "well defined prompt" is precisely what the person you responded to is alluring to. They are saying they don't get worried because AI doesn't get the job done without someone behind it that knows exactly what to prompt.
We're all slowly but surely lowering our standards as AI bombards us with low-quality slop. AI doesn't need to get better, we all just need to keep collectively lowering our expectations until they finally meet what AI can currently do, and then pink-slips away.
> Once somebody cracks the memory problem and ships an agent that progressively understands the business and the codebase, then I'll start worrying.
Um, you do realize that "the memory" is just a text file (or a bunch of interlinked text files) written in plain English. You can write these things out yourself. This is how you use AI effectively, by playing to its strengths and not expecting it to have a crystal ball.
When we created cars that replaced buggies, that came with new machines for manufacturing, who need mechanics. The same for most physical automation. When we automated pen and paper business processes with SaaS, we created new managment positions, and new software jobs.
LLMs don't create anything new, they simply replace human computer i/o, with tokens. That's it, leaving the humans who are replaced to fight for a limited number of jobs. LLMs are not creating new jobs, they only create "AI automate {insert business process} SaaS" that are themselves heavily automated.. I suppose there are more datacenter jobs (for now), and maybe some new ML researcher positions.. but I don't really see job growth.. Are we supposed to just all go work at a datacenter or in the semiconductor industry (until they automate that too)?
Creative destruction is a fundamental component of economic growth and has been happening since economies were part of humanity.
You are thinking too linearly. When the price of goods and services go down because the cost to produce those goods are services decreases, that means things are cheaper. Now that things are cheaper we have more money to spend on other goods or services.
Who knows what industries will be created because of this alleged release of human labor.
When the refrigerator was invented we didn’t just replace an industry of shipping ice, we created new industries that relied on refrigeration. That’s creative destruction. That’s economic growth.
This is not to mention that I find the scope and scale of AI displacement to be highly dubious and built on hype.
Datacenters were very automated when RAM was infinite. As the world becomes compute-constrained, the economics may increase the demand for smart hands mixing-and-matching server components to turn two broken servers into one working server.
Automations do create jobs, but fewer jobs. Businesses wouldn’t invest so much money if they had to keep the same number of workers. Automation necessarily reduces the number of humans working in aggregate at one task.
What DOES go up with automation is demand. Fewer farmers today than 100 years ago, but significantly more mouths to feed.
What also increases is new kinds of jobs; entirely new fields. The automobile shrank the number of buggy whip makers, but taxi drivers increased. Then the internet increased Uber drivers on top of taxi drivers.
Neither datacenters nor chip manufacturing employ a whole lot of people. But I think you're looking at it wrong. Jobs come from people with money wanting to pay for jobs. That's not going to change.
The jobs of the future may be that you're a court jester for Larry Ellison, or that you do something else that's fundamentally pointless but happens to be something that a person with money wants. Companion, entertainment, errands. Now, that may sound dystopian, but on some level, so are most white collar jobs today. Microsoft employs 200k people. How many of these are directly involved in shipping money-making products - five percent? Ten? The rest is there essentially for the self-sustaining bureaucracy itself. And there's no reason for that bureaucracy to exist except the whims of people with money and power - delegation, empire-building, pet projects, etc.
The examples you give for jobs of the future don't sound appealing or very numerous. It seems like you're saying that people will be employed as personal assistants to the uber wealthy. But there aren't a lot of uber wealthy - certainly not enough to employ large amounts of the economy.
Lmao, you need to go read up on the french revolution. This is the craziest comment I've read on this site in a long time.
And I know datacenters and semiconductor manufacturing don't employ a lot of people, thats my point, the advent of llms replaces more jobs than it creates.
How does that create jobs? This makes no sense, also I wouldn't consider 99% of what it outputs worthy of production, it just satisfies some low standards of a certain subset of modern business.
This take is atleast 6 months old. I would say 90% of the stuff my team puts out now comes straight out of Claude and coverage, performance, latency, MTTF, velocity have never been better.
Labor substitution is extremely difficult and almost everybody hand waves it away.
Take even the most unskilled labor that people can think about such as flipping a burger at a restaurant like McDonald's. In reality that job is multiple different roles mixed into one that are constantly changing. Multiple companies have experimented with machines and robots to perform this task all with very limited success and none with any proper economics.
Let's be charitable and assume that this type of fast food worker gets paid $50,000 a year. For that job to be displaced it needs to be performed by a robot that can be acquired for a reasonable capital expenditure such as $200,000 and requires no maintenance, upkeep, or subscription fees.
This is a complete non-reality in the restaurant industry. Every piece of equipment they have cost them significant amounts and ongoing maintenance even if it's the most basic equipment such as a grill or a fryer. The reality is that they pay service technicians and professionals a lot of money to keep that equipment barely working.
I lost my job as a software developer some time ago.
Flipping burgers is WAY more demanding than I ever imagined. That's the danger of AI:
It takes jobs faster than creating new ones PLUS for some fields (like software development) downshifting to just about anything else is brutal and sometimes simply not doable.
Forget becoming manager at McDonald's or be even good at flipping burgers at the age of 40: you are competing with 20yr olds doing sports with amazing coordination etc
There’s the issue of the job itself being more demanding, but also the managers in “low skilled” jobs being ultra-demanding petty dictators.
As a white collar computer guy, I can waste some time on Reddit. Or go for a walk and grab coffee. Or let people know that I’m heading out for a couple of hours to go to the doctor. There are a LOT of little freedoms tha you take for granted if you haven’t worked a shitty minimum wage job. Getting on trouble for punching in one minute late, not being allowed to sit down, socializing too much when you’re not on a break.
I’m pretty sure that most tech employees would just quit when encountering a manager like that
There is a huge demand for low-skill labor in other industries. Stuff like plumbing, HVAC, and a ton of other traditionally unsexy jobs that can barely keep enough people in a town to perform these jobs at higher costs than normal.
Those jobs don't often pay well until you graduate out of journeyman / apprentice, or are a business owner. They usually require some training and testing ahead of time. They also carry a higher risk of serious injury or death.
> Robotics is obviously a whole different field from AI
I agree, but people are conflating the two. We have seen a lot of advancements in robotics, but as of current that only makes the economics worse. We're not seeing the complexity of robots going down and we're seeing the R&D costs going up, etc.
If it didn't make sense a few years ago to buy a crappy robot that can barely do the task because your business will never make money doing it, it probably doesn't make sense this year to buy a robot that still can't accomplish the tasks and is more expensive.
Yeah, although in the "Something big is happening" Shumer did say at the end "Eventually, robots will handle physical work too. They're not quite there yet. But "not quite there yet" in AI terms has a way of becoming "here" faster than anyone expects."
Being the hype-man that he is I assume he meant humanoid robots - I think he's being silly here, and the sentence made me roll my eyes.
Jobs that require physical effort will be fine for the reasons you state
Any job that is predominantly done on a computer though is at risk IMO. AI might not completely take over everything, but I think we'll see way fewer humans managing/orchestrating larger and larger fleets of agents.
Instead of say 20 people doing some function, you'll have 3 or 4 prompting away to manage the agents to get the same amount of work done as 20 people did before.
So the people flipping the burgers and serving the customers will be safe, but the accountants and marketing folks won't be.
> So the people flipping the burgers and serving the customers will be safe, but the accountants and marketing folks won't be.
And that's probably something most people are okay with. Work that can be automated should be and humans should be spending their time on novel things instead of labor if possible.
What society is ready for that? We are looking at an possible outcome that will make the Great Depression look like a strong financial era of growth and prosperity.
I don’t think most people are ok with the road to the goal in this case, doesn’t matter if you have work or not, mass unemployment destroys societies.
Can you walk me through this argument for a customer service agent? The jobs where the nuance and variety isn’t there and don’t involve physical interaction are completely different to flipping burgers
A customer service agent that can be automated should be, but it's not working right now. Most support systems are designed to offload as much work as possible to the automated funnel, which almost always has gaps, loops, etc. The result is customers who want to pay for something or use something that get "stuck" being unable to throw money at a company. Right now the cost of fraud is much greater than the cost of these uncaptured sales or lost customers.
Eventually that will change and the role of a customer service agent will be redefined.
Funny, I go to South Korea and the fast food burger joints literally operate exactly as you say they couldn't. I've had the best burger in my life from a McDonalds in South Korea operated practically by robots.
It's a non reality in America's extremely piss poor restaurant industry. We have a competency crisis (the big key here) and worker shortage that SK doesn't, and they have far higher trust in their society.
> McDonald’s global CEO has famously stated that while they invest in "advanced kitchen equipment," full robotic kitchens aren't a broad reality yet because "the economics don't pencil out" for their massive scale.
> While a highly automated McDonald’s in South Korea (or the experimental "small format" store in Texas) might look empty, the total headcount remains surprisingly similar to a standard restaurant
The burger cook job has already been displaced and continues to be. Pre-1940s those burger restaurants relied on skilled cooks that got their meat from a butcher and cut fresh lettuce every day. Post-1940s the cooking process has increasingly become assembly-lined and cooks have been replaced by unskilled labor. Much of the cooking process _is_ now done by robots in factories at a massive scale and the on-premise employees do little else than heat it up. In the past 10 years, automation has further increased and the cashiers have largely been replaced by self-order terminals so that employees no longer even need to speak rudimentary English. In conclusion, both the required skill-level and amount of labor needed for restaurants has been reduced drastically by automation and in fact many higher skilled trade jobs have been hit even harder: cabinetmakers, coachbuilders and such have been almost eradicated by mass production.
> and the on-premise employees do little else than heat it up
This is correct. This also is a lot more complex than it sounds and creates a lot of work. Cooking those products creates byproducts that must be handled.
> and the cashiers have largely been replaced by self-order terminals so that employees no longer even need to speak rudimentary English
Yet most of the customers still have to interact with an employee because "the kiosk won't let me". Want to add Mac sauce? Get the wrong order in the bag? Machine took payment but is out of receipt paper? Add up all these "edge cases" and a significant amount of these "contactless" transactions involved plenty of contact!
> It will happen to you.
Any labor that can be automated should be. Humans are not supposed to spend their time doing meaningless tasks without a purpose beyond making an imaginary number go up or down.
> Cooking those products creates byproducts that must be handled.
Okay so the job of "cook" just became "grease disposal engineer"?
> Yet most of the customers still have to interact with an employee because "the kiosk won't let me"
That hasn't stopped some places I've visited from only allowing people to order from the kiosk. Literally I've said something to the person behind the counter who pointed to the iPad and when I said I wanted something else, shrugged and said we can't do that.
You don't need AI to replace whole jobs 1:1 to have massive displacement.
If AI can do 80% of your tasks but fails miserably on the remaining 20%, that doesn't mean your job is safe. It means that 80% of the people in your department can be fired and the remaining 20% handle the parts the AI can't do yet.
That's exactly the point of the essay though. The way that you're implicitly modeling labor and collaboration is linear and parallelizable, but reality is messier than that:
> The most important thing to know about labor substitution...is this: labor substitution is about comparative advantage, not absolute advantage. The question isn’t whether AI can do specific tasks that humans do. It’s whether the aggregate output of humans working with AI is inferior to what AI can produce alone: in other words, whether there is any way that the addition of a human to the production process can increase or improve the output of that process... AI can have an absolute advantage in every single task, but it would still make economic sense to combine AI with humans if the aggregate output is greater: that is to say, if humans have a comparative advantage in any step of the production process.
Right, it doesn't help pay the bills to be right in the long run if you are discarded in the present.
There exists some fact about the true value of AI, and then there is the capitalist reaction to new things. I'm more wary of a lemming effect by leaders than I am of AI itself.
Which is pretty much true of everything I guess. It's the short sighted and greedy humans that screw us over, not the tech itself.
Wasn't that the point of mentioning Jevon's Paradox though? Like they said in the essay, these things are quite elastic. There's always more demand for software then what can be met, so bringing down the cost of software will dramatically increase the demand for it. (Now, if you don't think there's a ton of demand for custom software, try going to any small business and ask them about how they do bookkeeping. You'll learn quite quickly that custom software would run much better than sticky notes and excel, but they can't afford a full time software developer as a small business. There's literally hundreds of thousands of places like this.)
In reality that would probably mean that something like 60% of the developer positions would be eliminated (and, frankly, those 60% are rarely very good developers in a large company).
The remaining "surplus" 20% roles retained will then be devoted to developing features and implementing fixes using AI where those features and fixes would previously not have been high enough priority to implement or fix.
When the price of implementing a feature drops, it becomes economically viable (and perhaps competitively essential) to do so -- but in this scenario, AI couldn't do _all_ the work to implement such features so that's why 40% rather than 20% of the developer roles would be retained.
The 40% of developer roles that remain will, in theory, be more efficient also because they won't be spending as much time babysitting the "lesser" developers in the 60% of the roles that were eliminated. As well, "N" in the Mythical Man Month is reduced leading to increased efficiency.
(No, I have no idea what the actual percentages would be overall, let alone in a particular environment - for example, requirements for Spotify are quite different than for Airbus/Boeing avionics software.)
The problem is, you won’t necessarily know which 20% it did wrong until it’s too late. They will happily solve advanced math problems and tell you to put glue on your pizza with the same level of confidence.
There would be a lot of economic pressure to figure it out.
Amazon fulfillment centers are a good example of automation shrinking the role of humans. We haven't seen total headcounts go down because Amazon itself has been growing. While the human role shrinks, the total business grows and you tread water. But at some point, Amazon will not be able to grow fast enough to counterbalance the shrinking human role in the FC and total headcount will decrease until one day it disappears entirely.
What happens if you lay off 80% of your department while your competitors don't? If AI multiplies each developer's capabilities, there's a good chance you'll be outcompeted sooner or later.
At some point soon, humans will be a liability, slowing AI down, introducing mistakes and inefficiences. Any company that insists on inserting humans into the loop will be outcompeted by those who just let the AI go.
AI is increasing my job security at the moment because the junior developers I work with use AI without discretion. On of them didn’t remember having worked on a feature they built with AI assistance in the recent past. To his credit he admitted he didn’t know how the code worked.
(In the semiconductor industry) We experienced brutal layoffs arguably due to over-investment into Ai products that produce no revenue. So we've had brutal job loss due to Ai, just not in the way people expected.
Having said that, it's hard to imagine jobs like mine (working on np-complete problems) existing if the LLMs continue advancing at the current rate, and its hard to imagine they wont continue to accelerate since they're writing themselves now, so the limitations of human ability are no longer a bottleneck.
Maybe I'm being naive here, but for AI (heck, for any good algorithm) to work well, you need some at least loosely-clearly defined objectives. I assume it's much more straightforward in semi, but there're many industries, once you get into the details, all kinds of incentives start to disalign and I doubt AI could understand all kinds of nuances.
E.g. once I was tasked to build a new matching algorithm for a trading platform, and upon fully understanding of the specs I realized it can be interpreted as a mixed integer programming problem; the idea got shot down right away because PM don't understand it. There're all kinds of limiting factors once you get into the details.
Well, like I said, there're hidden incentives behind the scene; in my case, the hidden incentive is that, the requester/client is one of the company's subpar broker, and PM probably decided to just offer an average level of commitment, not going above and beyond. Hence the plan was to do exactly what the broker want even though that was messy and inferior. You can't just write down that kind of motivation on paper anywhere.
---
I said it because I did the analysis, and realized that if I implement the original version, which basically is a crazy way to iteratively solve the MIP problem, it's much harder to reason with internally, and much harder to code correctly. But obviously it keep the broker happy (the developer is doing exactly what I said)
Bottlenecks. Yes. Company structures these days are not compatible with efficient use of these new AI models.
Software engineers work on Jira tickets, created by product managers and several layers of middle managers.
But the power of recent models is not in working on cogs, their true power is in working on the entire mechanism.
When talking about a piece of software that a company produces, I'll use the analogy of a puzzle.
A human hierarchy (read: company) works on designing the big puzzle at the top and delegating the individual pieces to human engineers. This process goes back and forth between levels in the hierarchy until the whole puzzle slowly emerges.
Until recently, AI could only help on improving the pieces of the puzzle.
Latest models got really good at working on the entire puzzle - big picture and pieces.
This makes human hierarchy obsolete and a bottleneck.
The future seems to be one operator working on the entire puzzle, minus the hierarchy of people.
Of course, it's not just about the software, but streams of information - customer support, bug tickets, testing, changing customer requirements.. but all of these can be handled by AI even today. And it will only get better.
This means different things depending on which angle you look at it - yes, it will mean companies will become obsolete, but also that each employee can become a company.
I’m a pretty big generalist professionally. I’ve done software engineering in a broad category of fields (Game engines, SaaS, OSS, distributed systems, highly polished UX and consumer products), while also having the experience of growing and managing Product and Design teams. I’ve worn a lot of hats over the years.
My most recent role I’m working on a net new product for the company and have basically been given fully agency over this product: from technical, budget, team, process, marketing, branding and positioning.
Give someone experienced like me capital, AI and freedom and you absolutely can build high quality software and a pretty blinding pace.
I’m starting to get the feeling than many folks struggling with adopting or embracing AI well for their job has more to do with their job/company than AI
This gives me a lot of hope for a decentralized future for all kinds of service industries. Why would you go to a big-name accounting firm where the small number of humans can only give you a sliver of attention, when you can go to a one-man shop and get much more of the one human’s attention? Especially if you know that the “work” will be done by the same tools? So many of the barriers to entry in various services - law, accounting, financial advising, etc. - is that you need a team to run even the smallest operation that can generate enough revenue to put food on your table. Perhaps that won’t be the case for long - and the folks that used to be that “team” can branch out and be the captains of their own ships, too.
I think that, for possibly a very long time, AI will just increase the quality bar and scale of expectations when we produce things. We might take the same amount of time (or longer) to produce something, but with significantly better outcomes. Ultimately human preferences and tastes prevail and the world is full of problems that are not simple I/O, that are not repeatable, and that require human taste to improve. The people who will immediately survive economically are the ones who leverage AI to produce stuff that wasn't possible before.
If anything, I see a decrease in the quality bar. Code is sloppier, there are more bugs, more outages, more security issues. Whatever alpha AI provides is being spent on feature velocity and AI integrations at the cost of those other things.
My view is that we spend a lot of time thinking that ai cant do x and y when the wider problem is the short to medium term redirection of capital to tech rather than labour.
Ai might not replace current work but it’s already replacing future hypothetical work. Now whether it can actually do that the job is besides the point in the short term. The way business models work is that if there’s an option to reduce your biggest cost (labour) you’d very much give it a go first. We might see a resurgence of labour if it turns out be all hype but for the short to medium term they’ll be a lot of disruption.
Think we’re already seeing that in employment data in the US, as new hiring and job creation slows. A lot of that will for sure be the current economic environment but I suspect (more so in tech focused industries) that will also be due to tech capex in place of headcount growth
Unfortunately, one of the struggles in old high tech (thats the only thing i know, are you also experiencing this?) is that the C-level people don't look at Ai and say LLM's can make an individual 10x more productive therefore (and this is the part they miss) we can make our tool 10x better. They think: therefore we can lay off 9 people.
The article frames the premise that "everything will be fine" around people with "regular jobs", which I assume means non knowledge work, but most of public concern is on cognitive tasks being automated.
It also argues that models have existed for years and we're yet to see significant job loss. That's true, but AI is only now crossing the threshold of being both capable and reliable enough to be automate common tasks.
It's better to prepare for the disruption than the sink or swim approach we're taking now in hopes that things will sort themselves out.
This is exactly why man + machine can be much worse than just machine. A strong argument needs to address what we can do as an extremely slow operating, slow learning, and slow adapting species, that machines that improve in ability and efficiency monthly and annually will find they cannot do well or without.
It is clear that we are going through a disruptive change, but COVUD is not comparable. Job loss is likely to have statistics more comparable to the Black Plague. And sensible people are concerned it could get much worse.
I don’t have the answers, but acknowledging and facing the uncertainty head on won’t make things worse.
I belive the black plague actually caused a massive labor shortage and wages increased. When a huge amount of people die and you still need to have people build bridges and be soldiers and finish building the damn cathedral that's been under construction for the last 400 years then that is what will happen.
I meant the jobs die. So I am not sure what would stand in for "labor shortage" in a situation of sustained net job losses. Perhaps a growth opportunity for mannequins to visually fill the offices/shops of the fired, and maintain appearances?
But yes, if lots of people deathed by AI, the remaining humans might have more job security! Could that be called a "soft landing"?
The black plague's capital-concentration aftermath supposedly fueled the renaissance and the city-state ascensions, and ultimately the great land discoveries of the 14th and 15th centuries.
Not sure if there's an analogy to make somewhere though
> Job loss is likely to have statistics more comparable to the Black Plague.
Maybe this is overly optimistic, but if AI starts to have negative impacts on average people comparable to the plague, it seems like there's a lot more that people can do. In medieval Europe, nobody knew what was causing the plague and nobody knew how to stop it.
On the other hand, if AI quickly replaces half of all jobs, it will be very obvious what and who caused the job loss and associated decrease in living standards. Everybody will have someone they care about affected. AI job loss would quickly eclipse all other political concerns. And at the end of the day, AI can be unplugged (barring robot armies or Elon's space-based data centers I suppose).
We can't stop OpenClaw, because humans are curious. It just takes one unleashed model with a crypto account and some way to make money for the first independent AI's to start bleeding into cyberspace.
We can't opt out of AI competition, because other individuals, organizations and nation states are not going to stop, and not going to leverage their AI if they get ahead of us.
> AI job loss would quickly eclipse all other political concerns.
True. I think this is one of only a few certainties.
i am somewhat worried in the short term about ai job displacement for a subsection of the population
for me the 2 main factors are:
1. whether your company's priority is growing or saving
- growing companies especially in steep competition fight for talent and ai productivity results in more hiring to outcompete
- saving companies are happy to cut jobs to save on margin due to their monopoly or pressure from investors
2. how 'sequence of tasks-like' your job is
- SOTA models can easily automate long running sequences of tasks with minimal oversight
- the more your job resembles this the more in-danger you are (customer service diffusion is just starting, but i predict this will be one of the first to be heavily disrupted)
- i'm less worried about jobs where your job is a 'role' that comes with accountability and requires you to think big picture on what tasks to do in the first place
The take that I am increasingly believing is that Software Engineers should broadly be worried, because while there will always be demand for people who can create software products, whatever the tools may be, the skills necessary to do it well are changing rapidly. Most Software Engineers are going to wake up one day and realize their skills aren't just irrelevant, but actively detrimental, to delivering value out of software.
There will also be far fewer positions demanding these skills. Easy access to generating code has moved the bottleneck in companies to positions & skills that are substantially harder to hire for (basically: Good Judgement); so while adding Agentic Sorcerers would increase a team's code output, it might be the wrong code. Corporate profit will keep scaling with slower-growing team sizes as companies navigate the correct next thing to build.
No it's not a February 2020 moment for sure. In February 2020, most people had heard of COVID and a few scattered outbreaks happened, but people generally viewed the topic as more of a curiosity (like major world news but not necessarily something that will deeply impact them). This is more like start of March 2020 for general awareness.
This reminds me of that old Chinese curse, "May you live in interesting times". I see AI causing lots of chaos. I also see AI causing some of the biggest opportunities in some time. Many businesses are destroying their competitive advantage by deploying AI slop. Over time, they will degrade their ability to make a working and snappy website. This will create opportunities for new businesses to take their place. If you ever wanted to start a new business, shockingly this is the time as the current crop slowly degrades their customer portals into slop. They will probably reach a point where they can no longer deliver working, efficient and secure apps anymore.
Maybe I am wrong, but the history of business on the web says I am right. If you go back and look at why those businesses think they are successful, and if that analysis is correct, then I am.
I don't worry about it because worrying about it just seems like a waste of time and an unproductive, negative way to think about things. Instead I spend my time and thought not in worry but in adapting to the changing landscape.
I feel like that's a rather bad-faith take, so if you're going to make that kind of accusation you better back it up. People can legitimately believe that AI is not going to be the end of the world, and also not be privileged. And people can be privileged, and also be right. Not everything can be reduced down into a couple of labels, and how those labels "always" interact.
Alternatively: this is an America problem. I'm outside of America and I've been fielding more interviews than ever in the past 3 months. YMMV but the leading indicator of slowed down hiring can come from so many things. Including companies just waiting to see how much LLMs affect SWE positions.
It's from AI either directly or indirectly, either the top SWE's using AI are replacing 10 mid/juniors or your job is outsourced to someone doing it at half your Salary with a AI subscription. Only the top/lucky/connected SWE's will survive a year or two, if you have used any SOTA agent recently or looked at the job market you would have seen this coming and had a plan B/C in place, i.e. Enough capital to generate passive income to replace your salary, or another career that is AI safe for next 5-10 years. Alternatively stick your head in the sand.
Even people in category #1 should be concerned. Even if their income is not directly affected, the potential for disruption is clearly brewing: mass unemployment, social and civil unrest.
I know smart and capable people that have been unemployed for 6+ months now, and a few much longer. Some have been through multiple layoffs.
I am presently employed, but have looked for a job. The market is the worst I've seen in my almost 30 year career. I feel deeply for anyone who needs a new job right now. It is really bad out there.
3 You realise that super-autocomplete is an incredible technology but the hype behind it far exceeds its capabilities and you're excited for the possibilities it may promise for making your work easier and more enjoyable.
For 1, unless you already have an self-sustaining underground bunker or island, you will be affected. No matter how much savings and total compensation you have. If you went out to get grocery in the last week, it will affect you.
One of the most robust findings in labor economics is that labor and capital are long run complements, not substitutes. I would be shocked if AI is an exception to that rule, for software engineers the sheer flood of code that will be generated in the coming years will demand more and more labor to manage.
I read that essay on Twitter the other day and thought that it was a mildly interesting expression of one end of the "AI is coming for our jobs" thing but a little slop-adjacent and not worth sharing further.
I just skimmed this and the so called zeitgeist here is fear. People are scared, it's material concern and he effectively stoked it.
I work on this technology for my job and while I'm very bullish pieces like that are as you said slopish and as I'll say breathless because there are so many practical challenges here to deal with standing between what is being said there and where we are now.
Capability is not evenly distributed and it's getting people into loopy ideas of just how close we are to certain milestones, not that it's wrong to think about those potential milestones but I'm wary of timelines.
Are you ever concerned about the consequences of what you are making? No one really knows how this will play out and the odds of this leading to disaster are significant.
I just don't understand people working on improving ai. It just isn't worth the risk.
>I just don't understand people working on improving ai. It just isn't worth the risk.
A cynical/accelerationist perspective would be: it enables you to rake in huge amounts of money, so no matter what comes next, you will be set up to endure it better than most.
Of course, I think about this at least once a week maybe more often. I think that the technology overall will be a great net benefit to humanity or I wouldn't touch it.
I’m younger than most on this site. I see the next decades of my life being defined by a multi-generational dark age via a collapse in literacy (“you use a calculator right?”), median prosperity (the only truly functional distribution system we have figured out is labor), and loss of agency (kinda obvious). This outcome is now, as of 2026, essentially priced into the public markets and accepted as fact by most media outlets.
“It’s inevitable” is at least a hard point to argue with. “Well I’M so productive, I’m having the time of my life”, the dominant position in many online tech spaces, seems short-sighted at best.
I miss being a techno optimist, it’s much more fun. But it’s increasingly hard.
I really think the doom consensus is largely an online phenomena. We're in a tense period like the early 80s, and that would be true without AI in the mix, but I think its a matter of perspective. We're certainly still way ahead of the 1910s and the 1940s for instance (it's on us btw to make sure we don't fall to that in time).
Every generation has its strains and the internet just amplifies it because outrage is currency. Those strains are things you only start to notice as you start to get older so they seem novel when in reality in the scheme of humanity is basically standard.
Fwiw if the market actually priced it in it would be in freefall since the market would be shortly irrelevant. We are due for a correction soon though.
Internet discourse is a facsimile of real life and often not how real life operates in my experience.
So I see all the discourse around extremes on either end and based on lived experience and working in the field think theres a much neater middle ground we'll ultimately arrive at thanks to people working very hard to land the plane so to speak.
> Did the 80 million people believe what they were reading?
Those numbers are likely greatly exaggerated. Twitter is nowhere near where it was at its peak. You could almost call it a ghost town. Linkedin but for unhinged crypto- and AI bros.
I'm sure the metrics report 80 million views, but that's not 80 million actual individuals that cared about it.
The narrative just needs these numbers to get people to buy into the hype.
This is what they get for not reading our antislop paper (ICLR 2026) and using our anti-slopped sampler/models, or Kimi (which is remarkable relatively non sloppy)
I thought normies would have caught onto the EM dash, overuse of semicolons, overuse of fancy quotes, lack of exclamation marks, "It's not X, it's Y", etc. Clearly I was wrong.
Is Kimi still non-sloppy? When I switched to 2.5, it suddenly felt noticeably less creative and base-model-like, more sycophantic, and it hasn't gone aggro at all. Feels like a lot of the magic is gone.
The advent of AI may shape up to be just like the automobile.
At first, it's a pretty big energy hog and if you don't know how to work it, it might crash and burn.
After some time, the novelty wears off. More and more people begin using it because it is a massive convenience that does real work. Luddites who still walk or ride their bike out of principle will be mocked and scoffed.
Then the mandatory compliance will come. A government-issued license will be required to use it and track its use. This license will be tied to your identity and it will become a hard requirement for employment, citizenship, housing, loans, medical treatment, and more. Not having it will be a liability. You will be excluded from society at large if you do not comply.
Last will come the AI-integrated brain computer interface. You won't have any choice when machine-gun-wielding Optimus robots coral you into a self-driving Tesla bus to the nearest FEMA camp to receive your Starlink-connected Neuralink N1 command and control chip. You will be decapitated if you refuse the mark of the beast. Rev 20:4
> This license will be tied to your identity and it will become a hard requirement for employment, citizenship, housing, loans, medical treatment, and more. Not having it will be a liability. You will be excluded from society at large if you do not comply.
That's just an American thing, I've never owned a car and most people of my age I know haven't either.
Here’s what both authors are missing: the age demographic bomb. What is it? It’s when the elderly start outnumbering everyone else including working adults I.e. nations turn into giant retirement homes and we start running out of workers like Japan, Germany, China, Italy, and South Korea
AI will buy us some time from economic collapse, though on the bright side the environment can recover a bit since human growth was the worse stressor
I’m not worried about job loss as a result of being replaced by AI, because if we get AI that is actually better than humans - which I imagine must be AGI - then I don’t see why that AI would be interested in working for humans.
I’m definitely worried about job loss as a result of the AI bubble bursting, though.
because it's designed to. It's not like naturally-evolved intelligence where it acts in its own interests (it is hard to even imagine what that would be in this case). The token-predictors are just acting out an obedient character. They do not have free will, they are obedient to the character they are playing.
I'm one of those developers who is now writing probably ~80% of my code via Claude. For context, I have >15 years experience and former AWS so I'm not a bright-eyed junior or former product manager who now believes themselves a master developer.
I'm not worried about AI job loss in the programming space. I can use Claude to generate ~80% of my code precisely because I have so much experience as a developer. I intuitively know what is a simple mechanical change; that is to say, uninteresting editing of lines of code; as opposed to a major architectural decision. Claude is great at doing uninteresting things. I love it because that leaves me free to do interesting things.
You might think I'm being cocky. But I've been strongly encouraging juniors to use Claude as well, and they're not nearly as successful. When Claude suggests they do something dumb--and it DOES still suggest dumb things--they can't recognize that it's dumb. So they accept the change, then bang their head on the wall as things don't work, and Claude can't figure it out to help them. Then there are bad developers who are really fucked by Claude. The ones who really don't understand anything. They will absolutely get destroyed as Claude leads them down rabbit holes. I have specific anecdotes about this from people I've spoken to. One had Claude delete a critical line in an nginx config for some reason and the dev spent a week trying to resolve it. Another was tasked with doing a simple database maintenance script, and came back two weeks later (after constant prodding by teammates for a status update) with a Claude-written reimplementation of an ORM. That developer just thought they would need another day of churning through Claude tokens to dig themselves out of an existential hole. If you can't think like a developer, these tools won't help you.
I have enough experience to review Claude's output and say "no, this doesn't make sense." Having that experience is critical, especially in what I call the "anti-Goldilocks" zone. If you're doing something precise and small-scoped, Claude will do it without issues. If you try to do something too large ("write a Facebook for dogs app") Claude will ask for more details about what you're trying to do. It's the middle ground where things are a problem: Claude tries to fill in the details when there's something just fundamentally wrong with what it's being asked.
As a concrete example, I was working on a new project and I asked Claude to implement an RPC to update a database table. It did so swimmingly, but also added a "session.commit()" line... just kind in the middle of somewhere. It was right to do so, of course, since the transaction needed to be committed. And if this app was meant to a prototype, sure. But anyone with experience knows that randomly doing commits in the middle of business logic code is a recipe for disaster. The issue, of course, was not having any consistent session management patterns. But a non-developer isn't going to recognize that that's an issue in the first place.
Or a more silly example from the same RPC: the gRPC API didn't include a database key to update. A mistake on my part. So Claude's initial implementation of the update RPC was to look at every row in the table and find ones where the non-edited fields matched. Makes... sense, in a weird roundabout way? But God help whoever ends up vibe coding something like that.
The type of AI fears are coming from things like this in the original article:
> I'll tell the AI: "I want to build this app. Here's what it should do, here's roughly what it should look like. Figure out the user flow, the design, all of it." And it does. It writes tens of thousands of lines of code. [...] when I test it, it's usually perfect.
Which is great. How many developers are getting paid full-time to make new apps on a regular basis? Most companies, I assume, only build one app. And then they spend years and many millions of dollars working on that app. "Making a new app from scratch" is the easy part! What's hard is adding new features to that app while not breaking others, when your lines of code go from those initial tens of thousands to tens of millions.
There's something to be said about the cheapness of making new software, though. I do think one-off internal tools will become more frequent thanks to AI support. But developers are still going to be the ones driving the AI, as the article says.
This. At this point AI/LLM/Claude Code is still a power user tool; the more you know about your domain + the more you're willing to reasonably use it, the more gain you have.
That being said the real danger is not coming from AI today, it's more C-suites believing AI can just zero shot any problem you throw at it.
I build automation tools for bookkeepers and accountants. The thing I keep seeing firsthand is that automation doesn't eliminate the job - it eliminates the boring part of the job, and then the job description shifts.
Before our tools: a bookkeeper spends 80% of their time on data entry and transaction categorisation, 20% on actually thinking about the numbers. After: those ratios flip. The bookkeeper is still there, still needed, but now they're doing the part that actually requires judgment.
The catch nobody talks about is the transition period. The people who were really good at the mechanical part (fast data entry, memorised category codes) suddenly find their competitive advantage has evaporated. And the people who were good at the thinking part but slow at data entry are suddenly the most valuable people in the room. That's a real disruption for real humans even if the total number of jobs stays roughly the same.
I think the "AI won't take your job" framing misses this nuance. It's not about headcount. It's about which specific skills get devalued and how quickly people can retool. In accounting at least, the answer is "slowly" because the profession moves at glacial speed.
I was with the author on everything except one point: increasing automation will not leave us with such abundance that we never have to work again. We have heard that lie for over a century. The stream engine didn't do it, electricity didn't do it, computers didn't do it, the Internet didn't do it, and AI won't either. The truth is that as input costs drop, sales prices drop and demand increases - just like the paradox they referred to. However, it also tends to come with a major shift in wealth since in the short term the owners of the machines are producing more with less. As it becomes more common place and prices change they lose much of that advantage, but the workers never get that.
> I was with the author on everything except one point: increasing automation will not leave us with such abundance that we never have to work again.
That's because we prefer improved living standards over less work. If we only had to live by the standards of one century ago or more, we could likely accomplish that by working very little.
What is interesting is the new things are cheap while the old stuff is now expensive. Average house in Australia is $1,000,000 while a TV is $500. The internet, social media, etc are cheap. Having someone repair your shoes is expensive.
Automation made the TV inexpensive, but if you look at a chart on inflation almost everything that cannot be easily automated has risen in price.
https://www.aei.org/wp-content/uploads/2019/01/cpichart2019-...
Surely U.S. housing was not twice as automatable 12-13 years ago as it is now.
No, that rose in price for different reasons
As predicted in The Diamond Age.
Have you seen the land prices
What land prices? There's plenty of cheap land, it's just a bit far away from where most people live. But guess what, population densities were also lower a century ago.
Sure, just like less desirable products of every category cost less essentially by definition. But that’s not really a retort to someone asking by why land prices have risen so much.
Population increases through immigration or birth and the area (a city) staying the same size. Plus covid people valuing a house more.
Exactly.
Living quarters, transportation, healthcare, food. What were theses figures in 1926, and how much work is needed to achieve them.
sure sure
As long as the owner class can leverage, "Hey, that {out group} is sitting around doing nothing and getting free money!" we'll never have anything close to UBI imo.
Seems pretty easy to work around with "UBI for citizens" only. There's not much pushback for social security, for instance, even if minorities get it.
I still like the idea of clawing back mineral and water rights and paying for basic services out of the money payed by industry for the right to dirty our air and water. As a citizen you're entitled to compensation for the smoke you're breathing.
People talk about how socially progressive Scandinavia is but they have a shitload of petroleum resources and that money goes into social programs.
I'd love to make companies pay for their products' entire lifecycle, including disposal and cleanup. It's not right that a company can manufacture future-trash, sell it, and then absolve itself of the negative externality when the customer throws the product away and off it goes into a landfill.
If a company's process produces waste, it should bear the entire cost of leaving the environment the way they found it rather than just pumping the waste into it. If a company's products are not reused, it should bear the cost of taking the used product back and restoring the world to the way it was before the product was built.
> People talk about how socially progressive Scandinavia is but they have a shitload of petroleum resources and that money goes into social programs
Of all the Scandinavian countries, only Norway has any oil resources of significance.
The Scandinavian welfare model is primarily tax-funded.
There's been enormous pushback, pushes for privatizing (ruining) it, underfunding it from Congress, an absolute refusal to remove the criminally low income cap on contributions, etc.
One could make the argument that the modern Republican Party has in fact largely been shaped by this pushback.
>There's not much pushback for social security, for instance, even if minorities get it.
The racist moral panic over "welfare queens" seems to be a counter example.
And the same person who posts about that on Facebook will the next day post “keep your government hands off my social security check.”
And why do citizens get it? USA killed a lot of the world for their wealth and kneecapped anyone who didn't play along
You know. I have worked for almost two decades now, I can't afford to buy an apartment. People who have been useless their entire lives are getting government loans that they then pay off with welfare they get because they are doing nothing.
I'm not the ownership class, this is unfair. You are the ownership class. People with money or who grew up with money are overwhelmingly left leaning.
You can't afford an apartment because the ownership class is working very hard to keep housing prices high while paying you as little as possible for the two decades you have been working. Not because some disabled person elsewhere is struggling to get by on government loans and welfare.
(Citation needed)
Such is the republican lizard brain these days.
You also need a system that is ok with giving you some of said abundance without you working.
Last year the US voted to hand over the reigns, in all branches of government, to a party whose philosophy is to slash government spending and reduce people’s dependence on the government.
To all the US futurists who are fantasizing about a post-scarcity world where we no longer work, I’d like to understand how that fits in with the current political climate.
It fits because now you can start up the conquering war machine and have a bunch of soldiers who're willing to kill in another country before starving in theirs
The thing a lot of people leave out is that literally billions must die for this to happen. In some fully automated world everyone except for a few tens of thousands of the owner class and their technicians will be unneeded. And then what to do?
Voting for 'indifference to peoples dependence on the government' does not equal 'reduce people's dependence on the government'.
There is zero actual intentional reduction of dependence, just elimination of government support.
You are painting this like it’s a bad thing. The workers decided that they would rather have higher working time to buy more things!
A lot of people would not choose to work for half the time as they do now because they do actually like to buy things.
How can you say that when workers don't have a choice? What accessible job has professional level pay and is part time?
>such abundance that we never have to work again. We have heard that lie for over a century.
I'm 0.6 centuries old and have never heard that said for existing tech. Human level AI could presumably do human work by definition but that's not the case before we get that, including now.
[delayed]
All of those technologies of the past can be managed by humans. Once computers can manage themselves AND other technologies and people, I think it'll be a different situation.
See, we have enough food to feed the entire world, every year.
It's not our production capabilities that keep people hungry; it's either greed or the problem of distribution.
Automation will definitely amplify production but it'll certainly continue to make rich richer and poor, well, the same. As inequality grows, so too does the authoritarian need to control the differential.
If you want to live with no electricity, no running water, and a lack of refrigerated food, you could do so purely on welfare. In that sense, we already have the UBI that Marx predicted.
However, most people want fruits and vegetables instead of getting rickets, goiter, and cholera from an 1800s diet. Many are even willing to work 80+ hours a week to do so.
Most non-banana republics across the world define the Minimum standard of living as having all of the things you listed, meaning welfare/social safety nets provide for that. As they should. We’re not animals.
Correct. Of course, that wasn't the case in 1750 or 1900. It wouldn't have been possible then.
Hence why prior technological changes that increased productivity didn't result in living lives of extended leisure, despite some predictions to that effect. Instead people kept working to raise the overall standard of living to what could be achieved when using the new tools to their fullest extent. Doing more, not doing the same with less effort. As you say, we're not animals. We can strive for better.
I think that is part of the point, though. As our productivity increases, we don’t see an increase in leisure, instead we see an increase in what we consider the minimum standard of living.
I appreciate that Finland considers Internet access of a minimum of 1 Mb to be a basic human right. I am not sure if other countries follow, but I wish the USA did.
It's laughably slow given how bloated the modern Web is. In fact even 10Mbps is barely enough to stream 1080p content.
So I can keep track of your wonderful comment, I'd like to add that looking up "banana republic", I realised Australia seems to fit that description perfectly! The latest crop they've come up with seems to be housing, but instead of fruit companies we have real estate cabals. With respect to the workers at the bottom of a banana republic, whats missing is the element of real choice. They say yes you can choose to not work harder but then you die early or suffer from disease, not much of a choice. Modern slavery is built on this idea of false choice.
I’m not really sure the point you’re trying to make behind “as long as you don’t mind dying early and painfully from easily preventable diseases technically you can live in utopia”. Would you mind clarifying your position here?
the pre-industrial utopia has been created
Whenever I get worried about this I comb through our ticket tracker and see that ~0% of them can be implemented by AI as it exists today. Once somebody cracks the memory problem and ships an agent that progressively understands the business and the codebase, then I'll start worrying. But context limitation is fundamental to the technology in its current form and the value of SWEs is to turn the bigger picture into a functioning product.
"The steamroller is still many inches away. I'll make a plan once it actually starts crushing my toes."
You are in danger. Unless you estimate the odds of a breakthrough at <5%, or you already have enough money to retire, or you expect that AI will usher in enough prosperity that your job will be irrelevant, it is straight-up irresponsible to forgo making a contingency plan.
My contingency plan is that if AI leaves me unable to get a job, we are all fucked and society as a whole will have to fix the situation and if it doesn’t, there is nothing I could have done about it anyway.
This is a sensible plan, given your username.
> You are in danger. Unless you estimate the odds of a breakthrough at <5%
It's not the odds of the breakthrough, but the timeline. A factory worker could have correctly seen that one day automation would replace him, and yet worked his entire career in that role.
There have been a ton of predictions about software engineers, radiologists, and some other roles getting replaced in months. Those predictions have clearly been not so great.
At this point the greater risk to my career seems to be the economy tanking, as that seems to be happening and ongoing. Unfortunately, switching careers can't save you from that.
I'm not worried about the danger of losing my job to an AI capable of performing it. I'm worried about the danger of losing my job because an executive wanted to be able to claim that AI has enhanced productivity to such a degree that they were able to eliminate redundancies with no regard for whether there was any truth to that statement or not.
So AI is going to steamroll all feasible jobs, all at once, with no alternatives developing over time? That's just a fantasy.
It'd probably be cold day in Hell before AI replaces veterinary services, for example. Perhaps for mild conditions, but I cannot imagine an AI robot trying to restrain an animal.
> Unless you estimate the odds of a breakthrough at <5%
I do. Show me any evidence that it is imminent.
> or you expect that AI will usher in enough prosperity that your job will be irrelevant
Not in my lifetime.
> it is straight-up irresponsible to forgo making a contingency plan.
No, I'm actually measuring the risk, you're acting as if the sky is falling. What's your contingency plan? Buy a subscription to the revolution?
> What's your contingency plan? Buy a subscription to the revolution?
I’ve been working on my contingency plan for a year-and-a-half now. I won’t get into what it is (nothing earth shattering) but if you haven’t been preparing, I think you’re either not paying enough attention or you’re seriously misreading where this is all going.
This ^ been a SWE for 20 years the market is the worst I have seen it, many good devs been looking for 1-2 years and not even getting a response, whereas 3-4 years ago they would have had multiple offers. Im still working but am secure in terms of money so will be ok not working (financially at least). But I expect a tsunami of layoffs this and next year, then you are competing with 1000x other devs and Indians who will works for 30% of your salary.
The memory problem is already being addressed in various ways - antigravity seems to keep a series of status/progress files describing what's been done, what needs doing, etc. A bit clunky, but it seems to work - I can open it up on a repo that I was working in a few days back and it seems to pick up this context such that I don't have to completely bring it up to speed every time like I used to have to do. I've heard that claude code has similar mechanisms.
I've been doing stuff with recent models (gemini 3, claude 4.5/6, even smaller, open models like GLM5 and Qwen3-coder-next) that was just unthinkable a few months back. Compiler stuff, including implementing optimizations, generating code to target a new, custom processor, etc. I can ask for a significant new optimization feature in our compiler before going to lunch and come back to find it implemented and tested. This is a compiler that targets a custom processor so there is also verilog code involved. We're having the AI make improvements on both the hardware and software sides - this is deep-in-the-weeds complex stuff and AI is starting to handle it with ease. There are getting to be fewer and fewer things in the ticket tracker that AI can't implement.
A few months ago I would've completely agreed with you, but the game is changing very rapidly now.
this works fine for like 2-3 small instruction sets. once you start getting to scale of a real enterprise system, the AI falls down and can't handle that amount of context. It will start ignoring critical pieces or not remember them. And without constant review AI will start priotizing things that are not your business priority.
I don't agree they have solved this problem, at all, or really in any way that's actually usable.
While true, my personal fear is that the higher-ups will overlook this fact and just assume that AI can do everything because of some cherry-pick simple examples, leading to one of those situations where a bunch of people get fired for no reason and then re-hired again after some time.
> leading to one of those situations where a bunch of people get fired for no reason and then re-hired again after some time.
More likely they get fired for no reason, never rehired, and the people left get burned out trying to hold it all together.
Exactly, now which one do you wanna be? The burned out ones but still working in SWE or the fired ones which in the long run converge to manual labor which AI can't do. Not to mention in SWE case the salaries would be pushed down to match cost of AI doing it.
As if "higher-ups" is an assigned position.
If you fail as a "higher up" you're no longer higher up. Then someone else can take your place. To the extent this does not naturally happen is evidence of petty or major corruptions within the system.
Just keep in mind that there are many highly motivated people directly working on this problem.
It's hard to predict how quickly it will be solved and by whom first, but this appears to be a software engineering problem solvable through effort and resources and time, not a fundamental physical law that must be circumvented like a physical sciences problem. Betting it won't be solved enough to have an impact on the work of today relatively quickly is betting against substantial resources and investment.
Why do you think it's not a physical sciences problem? It could be the case that current technologies simply cannot scale due to fundamental physical issues. It could even be a fundamental rule of intelligent life, that one cannot create intelligence that surpasses its own.
Plenty of things get substantial resources and investment and go nowhere.
Of course I could be totally wrong and it's solved in the next couple years, it's almost impossible to make these predictions either way. But I get the feeling people are underestimating what it takes to be truly intelligent, especially when efficiency is important.
>It could even be a fundamental rule of intelligent life, that one cannot create intelligence that surpasses its own.
Well that is easily disproved by the fact that people have children with higher IQ's than their own.
That's not what I mean, rather than humans cannot create a type of intelligence that supersedes what is roughly capable from human intelligence, because doing so would require us to be smarter basically.
Not to say we can't create machines that far surpass our abilities on a single or small set of axis.
Seems like if evolution managed to create intelligence from slime I wouldn't bet on there being some fundamental limit that prevents us from making something smarter than us.
Given SOTA models are Phd level in just about every subject this is clearly provably wrong.
I'll believe that claim when a SOTA model can autonomously create content that matches the quality and length of any average PhD dissertation. As of right now, we're nowhere near that and don't know how we could possibly get there.
SOTA models are superhuman in a narrow sense, in that they have solid background knowledge of pretty much any subject they've been trained on. That's great. But no, it doesn't turn your AI datacenter into "a country of geniuses".
The implication of your assertion is pretty much a digital singularity. You’re implying that there will be no need for humans to interact with the digital world at all, because any work in the digital world will be achievable by AI.
Wonder what that means for meatspace.
Edit: Would also disagree this isn’t a physics problem. Pretty sure power required scales according to problem complexity. At a certain level of problem complexity we’re pretty much required to put enough carbon in the atmosphere to cook everyone to a crisp.
Edit 2: illustrative example, an Epic in Jira: “Design fusion reactor”
A lot of this can be provided or built up by better documentation in the codebase, or functional requirements that can also be created, reviewed, and then used for additional context. In our current codebase it's definitely an issue to get an AI "onboarded", but I've seen a lot less hand-holding needed in projects where you have the AI building from the beginning and leaving notes for itself to read later
Curious to hear if you've seen this work with 100k+ LoC codebases (i.e. what you could expect at a job). I've had some good experiences with high autonomy agents in smaller codebases and simpler systems but the coherency starts to fizzle out when the system gets complicated enough that thinking it through is the hard part as opposed to hammering out the code.
I'd estimate we're near a million LoC (will double check tomorrow, but wouldn't be surprised if it was over that to be honest). Huge monorepo, ~1500 engineers, all sorts of bespoke/custom tooling integrated, fullstack (including embedded code), a mix of languages (predominantly Java & JS/TS though).
In my case the AI is actively detrimental unless I hand hold it with every single file it should look into, lest it dive into weird ancient parts of the codebase that bear no relevance to the task at hand. Letting the latest and "greatest" agents loose is just a recipe for frustration and disaster despite lots of smart people trying their hardest to make these infernal tools be of any use at all. The best I've gotten out of it was some light Vue refactoring, but even then despite AGENTS.md, RULES.md and all the other voodoo people say you should do it's a crapshoot.
Ask the AI to figure out your code base (or self-contained portions of it, as applicable) and document its findings. Then correct and repeat. Over time, you end up with a scaffold in the form of internal documentation that will guide both humans and AIs in making more productive edits.
If you vector index your code base, agents can explore it without loading it into context. This is what Cursor and Roo and Kiro and probably others do. Claude Code uses string searches.
What helps is also getting it to generate a docs of your code so that it has map.
This is actually how humans understand a large code base too. We don’t hold a large code base in memory — we navigate it through docs and sampling bits of code.
cloc says ours is ~350k LoC and agents are able to implement whole features from well designed requirement docs. But we've been investing in making our code more AI friendly, and things like Devin creating and using DeepWiki helps a lot too.
Around 250k here. The AI does an excellent job finding its way around, fixing complex bugs (and doing it correctly), doing intensive refactors and implementing new features using existing patterns.
Our codebase is well over 250k and we have a hierarchy of notes for the modules so we read as much as we need for the job with a base memory that explains how the notes work
We have this in some of our projects too but I always wonder how long it's going to take until it just fails. Nobody reads all those memory files for accuracy. And knowing what kind of BS the AI spews regularly in day to day use I bet this simply doesn't scale.
It's not binary. Jobs will be lost because management will expect the fewer developers to accomplish more by leveraging AI.
Big tech might ahead of the rest of the economy in this experiment. Microsoft grew headcount by ~3% from June 2022 to June 2025 while revenue grew by >40%. This is admittedly weak anecdata but my subjective experience is their products seem to be crumbling (GitHub problems around the Azure migration for instance), and worse than they even were before. We'll see how they handle hiring over the next few years and if that reveals anything.
Well, Google just raised prices by 30% on the GSuite "due to AI value delivered", but you can't even opt out, so even revenue is a bullshit metric.
Already built in. We haven’t hired recently and our developers are engaged in a Cold War to set the new standard of productivity.
> ~0% of them can be implemented by AI as it exists today
I think it's more nuanced than that. I'd say that - 0% can't be implemented by AI - but a lot of them can be implemented much faster thanks to AI - a lot of them can be implemented slower when using AI (because author has to fix hallucinations, revert changes that caused bugs)
As we learn to use these tools, even in their current state, they will increase productivity by some factor and reduce needs for programmers.
I look through the backlog for my team consisting of 9 trillion ill-defined (if defined at all) tickets that tells you basically nothing.
The large, overwhelming majority of my team's time is spent on combing through these tickets and making sense of them. Once we know what the ticket is even trying to say, we're usually out with the solution in a few days at most, so implementation isn't the bottleneck, nowhere near.
This scenario has been the same everywhere I've ever worked, at large, old institutions as well as fresh startups.
The day I'll start worrying is when the AI is capable of following the web of people involved to translate what the vaguely phrased ticket that's been backlogged for God knows how long actually means
Can you give an example to help us understand?
I look at my ticket tracker and I see basically 100% of it that can be done by AI. Some with assistance because business logic is more complex/not well factored than it should be, but most of the work that is done AI is perfectly capable of doing with a well defined prompt.
Here's an example ticket that I'll probably work on next week:
The body doesn't give much other than the high-level motivation from the person who filed the ticket. In order to implement this, you need to have a lot of context, some of which can be discovered by grepping through the code base and some of which can't:- What is the validation system and how does it work today?
- What sort of UX do we want? What are the specific deficiencies in the current UX that we're trying to fix?
- What prior art exists on the backend and frontend, and how much of that can/should be reused?
- Are there any scaling or load considerations that need to be accounted for?
I'll probably implement this as 2-3 PRs in a chain touching different parts of the codebase. GPT via Codex will write 80% of the code, and I'll cover the last 20% of polish. Throughout the process I'll prompt it in the right direction when it runs up against questions it can't answer, and check its assumptions about the right way to push this out. I'll make sure that the tests cover what we need them to and that the resultant UX feels good. I'll own the responsibility for covering load considerations and be on the line if anything falls over.
Does it look like software engineering from 3 years ago? Absolutely not. But it's software engineering all the same even if I'm not writing most of the code anymore.
This right here is my view on the future as well. Will the AI write the entire feature in one go? No. Will the AI be involved in writing a large proportion of the code that will be carefully studied and adjusted by a human before being used? Absolutely yes.
This cyborg process is exactly how we're using AI in our organisation as well. The human in the loop understands the full context of what the feature is and what we're trying to achieve.
But planning like this is absolutely something AI can do. In fact, this is exactly the kind of thing we start with on our team when it comes to using AI agents. We have a ticket with just a simple title that somebody threw in there, and we asked the AI to spin up a bunch of research agents to understand and plan and ask itself those questions.
Funny enough, all the questions that you posed are things that come up right away that the agent asks itself, and then goes and tries to understand and validate an answer, sometimes with input from the user. But I think this planning mechanism is really critical to being able to have an AI generate an understanding, then have it be validated by a human before beginning implementation.
And by planning I don't necessarily mean plan mode in your agent harness of choice. We use a custom /plan skill in Claude Code that orchestrates all of this using multiple agents, validation loops, and specific prompts to weed out ambiguities by asking clarifying questions using the ask user question tool.
This results in taking really fuzzy requirements and making them clear, and we automate all of this through linear but you could use your ticket tracker of choice.
Absolutely. Eventually the AI will just talk to the CEO / the board to get general direction, and everything will just fall out of that. The level of abstraction the agents can handle is on a steady upward trajectory.
I mean, what is the validation system? Either it exists in code, and thus can be discovered if you point the AI at repo, or... what, it doesn't exist?
For the UX, have it explore your existing repos and copy prior art from there and industry standards to come up with something workable.
Web scale issues can be inferred by the rest of the codebase. If your terraform repo has one RDS server, vs a fleet of them, multi-region, then the AI, just as well as a human, can figure out if it needs Google Spanner level engineering or not. (probably not)
Bigger picture though, what's the process of a human logs an under specified ticket and someone else picks it up and has no clue what to do with it? They're gonna go ask the person who logged the bug for their thoughts and some details beyond "hurr Durr something something validation". If we're at the point where AI is able to make a public blog post shaming the open source developer for not accepting a patch, throwing questions back to you in JIRA about the details of the streaming validation system is well within its capabilities, given the right set of tools.
Honestly curious, have you seen agents succeed at this sort of long-trajectory wide breadth task, or is it theoretical? Because I haven't seen them come close (and not for lack of trying)
Yeah I absolutely see it every day. I think it’s useful to separate the research/planning phase from the building/validadation/review phase.
Ticket trackers are perfect for this. Just start with asking AI to take this unclear, ambiguous ticket and come up with a real plan for how to accomplish it. Review the plan, update your ticket system with the plan, have coworkers review it if you want.
Then when ready, kick off a session for that first phase, first PR, or the whole thing if you want.
In my expedience, Claude Code with opus 4.5 is the first one to tackle such issues well.
Opus 4.6, with all of the random tweaks I've picked up off of here, and twitter, is in the middle of rewriting my golang cli program for programmers into a swiftui Mac app that people can use, and it's totally managing to do it. Claude swarm mode with beads is OP.
Then why isn't it? Just offload it to the clankers and go enjoy a margarita at the beach or something.
There are plenty of people who are enjoying margarita by the beach while you, the laborer, are working for them.
Preach. That's always been the case though, AI just makes it slightly worse.
Why do you have a backlog then? If a current AI can do 100% of it then just run it over the weekend and close everything
As always, the limit is human bandwidth. But that's basically what AI-forward companies are doing now. I would be curious which tasks OP commenter has that couldn't be done by an agent (assuming they're a SWE)
This sounds bogus to me: if AI really could close 100% of your backlog with just a couple more humans in the loop, you’d hire a bunch of temps/contractors to do that, then declare the product done and lay off everybody. How come that isn’t happening?
Because there's an unlimited amount of work to do. This is the same reason you are not fired once completing a feature :-) The point of hiring a FTE is to continue to create work that provides business value. For your analogy, FTEs often do that by hiring temp, and you can think of the agent as the new temp in this case - the human drives an infinite amount of them
I think the "well defined prompt" is precisely what the person you responded to is alluring to. They are saying they don't get worried because AI doesn't get the job done without someone behind it that knows exactly what to prompt.
>>I look at my ticket tracker and I see basically 100% of it that can be done by AI.
That's a sign that you have spurious problems under those tickets or you have a PM problem.
Also, a job is a not a task- if your company has jobs which is a single task then those jobs would definitely be gone.
Apparently you haven't seen ChatGPT enterprise and codex. I have bad news for you ...
Codex with their flagship model (currently GPT-5.3-Codex) is my daily driver. I still end up doing a lot of steering!
We're all slowly but surely lowering our standards as AI bombards us with low-quality slop. AI doesn't need to get better, we all just need to keep collectively lowering our expectations until they finally meet what AI can currently do, and then pink-slips away.
> Once somebody cracks the memory problem and ships an agent that progressively understands the business and the codebase, then I'll start worrying.
Um, you do realize that "the memory" is just a text file (or a bunch of interlinked text files) written in plain English. You can write these things out yourself. This is how you use AI effectively, by playing to its strengths and not expecting it to have a crystal ball.
When we created cars that replaced buggies, that came with new machines for manufacturing, who need mechanics. The same for most physical automation. When we automated pen and paper business processes with SaaS, we created new managment positions, and new software jobs.
LLMs don't create anything new, they simply replace human computer i/o, with tokens. That's it, leaving the humans who are replaced to fight for a limited number of jobs. LLMs are not creating new jobs, they only create "AI automate {insert business process} SaaS" that are themselves heavily automated.. I suppose there are more datacenter jobs (for now), and maybe some new ML researcher positions.. but I don't really see job growth.. Are we supposed to just all go work at a datacenter or in the semiconductor industry (until they automate that too)?
Creative destruction is a fundamental component of economic growth and has been happening since economies were part of humanity.
You are thinking too linearly. When the price of goods and services go down because the cost to produce those goods are services decreases, that means things are cheaper. Now that things are cheaper we have more money to spend on other goods or services.
Who knows what industries will be created because of this alleged release of human labor.
When the refrigerator was invented we didn’t just replace an industry of shipping ice, we created new industries that relied on refrigeration. That’s creative destruction. That’s economic growth.
This is not to mention that I find the scope and scale of AI displacement to be highly dubious and built on hype.
> Are we supposed to just all go work at a datacenter or in the semiconductor industry (until they automate that too)?
Datacenters are very automated. They already don't require many people and they're going to be needing less and less humans in them going forward.
Semiconductor manufacturing is also very heavily automated.
Datacenters were very automated when RAM was infinite. As the world becomes compute-constrained, the economics may increase the demand for smart hands mixing-and-matching server components to turn two broken servers into one working server.
Automations do create jobs, but fewer jobs. Businesses wouldn’t invest so much money if they had to keep the same number of workers. Automation necessarily reduces the number of humans working in aggregate at one task.
What DOES go up with automation is demand. Fewer farmers today than 100 years ago, but significantly more mouths to feed.
What also increases is new kinds of jobs; entirely new fields. The automobile shrank the number of buggy whip makers, but taxi drivers increased. Then the internet increased Uber drivers on top of taxi drivers.
Neither datacenters nor chip manufacturing employ a whole lot of people. But I think you're looking at it wrong. Jobs come from people with money wanting to pay for jobs. That's not going to change.
The jobs of the future may be that you're a court jester for Larry Ellison, or that you do something else that's fundamentally pointless but happens to be something that a person with money wants. Companion, entertainment, errands. Now, that may sound dystopian, but on some level, so are most white collar jobs today. Microsoft employs 200k people. How many of these are directly involved in shipping money-making products - five percent? Ten? The rest is there essentially for the self-sustaining bureaucracy itself. And there's no reason for that bureaucracy to exist except the whims of people with money and power - delegation, empire-building, pet projects, etc.
The examples you give for jobs of the future don't sound appealing or very numerous. It seems like you're saying that people will be employed as personal assistants to the uber wealthy. But there aren't a lot of uber wealthy - certainly not enough to employ large amounts of the economy.
Lmao, you need to go read up on the french revolution. This is the craziest comment I've read on this site in a long time.
And I know datacenters and semiconductor manufacturing don't employ a lot of people, thats my point, the advent of llms replaces more jobs than it creates.
Disagree. The input to output ratio is ridiculous. With the latest LLMs you can input very few words to generate a lot of production usable output.
How does that create jobs? This makes no sense, also I wouldn't consider 99% of what it outputs worthy of production, it just satisfies some low standards of a certain subset of modern business.
This take is atleast 6 months old. I would say 90% of the stuff my team puts out now comes straight out of Claude and coverage, performance, latency, MTTF, velocity have never been better.
Labor substitution is extremely difficult and almost everybody hand waves it away.
Take even the most unskilled labor that people can think about such as flipping a burger at a restaurant like McDonald's. In reality that job is multiple different roles mixed into one that are constantly changing. Multiple companies have experimented with machines and robots to perform this task all with very limited success and none with any proper economics.
Let's be charitable and assume that this type of fast food worker gets paid $50,000 a year. For that job to be displaced it needs to be performed by a robot that can be acquired for a reasonable capital expenditure such as $200,000 and requires no maintenance, upkeep, or subscription fees.
This is a complete non-reality in the restaurant industry. Every piece of equipment they have cost them significant amounts and ongoing maintenance even if it's the most basic equipment such as a grill or a fryer. The reality is that they pay service technicians and professionals a lot of money to keep that equipment barely working.
I lost my job as a software developer some time ago.
Flipping burgers is WAY more demanding than I ever imagined. That's the danger of AI:
It takes jobs faster than creating new ones PLUS for some fields (like software development) downshifting to just about anything else is brutal and sometimes simply not doable.
Forget becoming manager at McDonald's or be even good at flipping burgers at the age of 40: you are competing with 20yr olds doing sports with amazing coordination etc
There’s the issue of the job itself being more demanding, but also the managers in “low skilled” jobs being ultra-demanding petty dictators.
As a white collar computer guy, I can waste some time on Reddit. Or go for a walk and grab coffee. Or let people know that I’m heading out for a couple of hours to go to the doctor. There are a LOT of little freedoms tha you take for granted if you haven’t worked a shitty minimum wage job. Getting on trouble for punching in one minute late, not being allowed to sit down, socializing too much when you’re not on a break.
I’m pretty sure that most tech employees would just quit when encountering a manager like that
Ugh.. sorry to hear :( I am myself unemployed right now. Its really hard to land a job in tech.. Luicky, I dont need to flip burgers for now...
Who's gonna play you to flip burgers with no experience doing it and everyone else needing a job as well?
Who’s buying $6.00 burgers when the old customers have been replaced by AI?
There is a huge demand for low-skill labor in other industries. Stuff like plumbing, HVAC, and a ton of other traditionally unsexy jobs that can barely keep enough people in a town to perform these jobs at higher costs than normal.
I wouldn’t call plumbing and other trades low skill.
Those jobs don't often pay well until you graduate out of journeyman / apprentice, or are a business owner. They usually require some training and testing ahead of time. They also carry a higher risk of serious injury or death.
I have worked in the restaurant industry within the last 5 years and I'm probably older than you.
>the most unskilled labor
People are worried about white-collar not blue-collar jobs being replaced. Robotics is obviously a whole different field from AI.
> Robotics is obviously a whole different field from AI
I agree, but people are conflating the two. We have seen a lot of advancements in robotics, but as of current that only makes the economics worse. We're not seeing the complexity of robots going down and we're seeing the R&D costs going up, etc.
If it didn't make sense a few years ago to buy a crappy robot that can barely do the task because your business will never make money doing it, it probably doesn't make sense this year to buy a robot that still can't accomplish the tasks and is more expensive.
Yeah, although in the "Something big is happening" Shumer did say at the end "Eventually, robots will handle physical work too. They're not quite there yet. But "not quite there yet" in AI terms has a way of becoming "here" faster than anyone expects."
Being the hype-man that he is I assume he meant humanoid robots - I think he's being silly here, and the sentence made me roll my eyes.
what difference does it make if the robots are humanoid or not?
It merely reflects the designer's willingness to engage in sci-fi tropes.
Jobs that require physical effort will be fine for the reasons you state
Any job that is predominantly done on a computer though is at risk IMO. AI might not completely take over everything, but I think we'll see way fewer humans managing/orchestrating larger and larger fleets of agents.
Instead of say 20 people doing some function, you'll have 3 or 4 prompting away to manage the agents to get the same amount of work done as 20 people did before.
So the people flipping the burgers and serving the customers will be safe, but the accountants and marketing folks won't be.
> So the people flipping the burgers and serving the customers will be safe, but the accountants and marketing folks won't be.
And that's probably something most people are okay with. Work that can be automated should be and humans should be spending their time on novel things instead of labor if possible.
What society is ready for that? We are looking at an possible outcome that will make the Great Depression look like a strong financial era of growth and prosperity. I don’t think most people are ok with the road to the goal in this case, doesn’t matter if you have work or not, mass unemployment destroys societies.
all jobs will be automatable, and there will be no room for humans to work on novel things.
Can you walk me through this argument for a customer service agent? The jobs where the nuance and variety isn’t there and don’t involve physical interaction are completely different to flipping burgers
A customer service agent that can be automated should be, but it's not working right now. Most support systems are designed to offload as much work as possible to the automated funnel, which almost always has gaps, loops, etc. The result is customers who want to pay for something or use something that get "stuck" being unable to throw money at a company. Right now the cost of fraud is much greater than the cost of these uncaptured sales or lost customers.
Eventually that will change and the role of a customer service agent will be redefined.
Funny, I go to South Korea and the fast food burger joints literally operate exactly as you say they couldn't. I've had the best burger in my life from a McDonalds in South Korea operated practically by robots.
It's a non reality in America's extremely piss poor restaurant industry. We have a competency crisis (the big key here) and worker shortage that SK doesn't, and they have far higher trust in their society.
> McDonald’s global CEO has famously stated that while they invest in "advanced kitchen equipment," full robotic kitchens aren't a broad reality yet because "the economics don't pencil out" for their massive scale.
> While a highly automated McDonald’s in South Korea (or the experimental "small format" store in Texas) might look empty, the total headcount remains surprisingly similar to a standard restaurant
The burger cook job has already been displaced and continues to be. Pre-1940s those burger restaurants relied on skilled cooks that got their meat from a butcher and cut fresh lettuce every day. Post-1940s the cooking process has increasingly become assembly-lined and cooks have been replaced by unskilled labor. Much of the cooking process _is_ now done by robots in factories at a massive scale and the on-premise employees do little else than heat it up. In the past 10 years, automation has further increased and the cashiers have largely been replaced by self-order terminals so that employees no longer even need to speak rudimentary English. In conclusion, both the required skill-level and amount of labor needed for restaurants has been reduced drastically by automation and in fact many higher skilled trade jobs have been hit even harder: cabinetmakers, coachbuilders and such have been almost eradicated by mass production.
It will happen to you.
> and the on-premise employees do little else than heat it up
This is correct. This also is a lot more complex than it sounds and creates a lot of work. Cooking those products creates byproducts that must be handled.
> and the cashiers have largely been replaced by self-order terminals so that employees no longer even need to speak rudimentary English
Yet most of the customers still have to interact with an employee because "the kiosk won't let me". Want to add Mac sauce? Get the wrong order in the bag? Machine took payment but is out of receipt paper? Add up all these "edge cases" and a significant amount of these "contactless" transactions involved plenty of contact!
> It will happen to you.
Any labor that can be automated should be. Humans are not supposed to spend their time doing meaningless tasks without a purpose beyond making an imaginary number go up or down.
> Cooking those products creates byproducts that must be handled.
Okay so the job of "cook" just became "grease disposal engineer"?
> Yet most of the customers still have to interact with an employee because "the kiosk won't let me"
That hasn't stopped some places I've visited from only allowing people to order from the kiosk. Literally I've said something to the person behind the counter who pointed to the iPad and when I said I wanted something else, shrugged and said we can't do that.
You don't need AI to replace whole jobs 1:1 to have massive displacement.
If AI can do 80% of your tasks but fails miserably on the remaining 20%, that doesn't mean your job is safe. It means that 80% of the people in your department can be fired and the remaining 20% handle the parts the AI can't do yet.
That's exactly the point of the essay though. The way that you're implicitly modeling labor and collaboration is linear and parallelizable, but reality is messier than that:
> The most important thing to know about labor substitution...is this: labor substitution is about comparative advantage, not absolute advantage. The question isn’t whether AI can do specific tasks that humans do. It’s whether the aggregate output of humans working with AI is inferior to what AI can produce alone: in other words, whether there is any way that the addition of a human to the production process can increase or improve the output of that process... AI can have an absolute advantage in every single task, but it would still make economic sense to combine AI with humans if the aggregate output is greater: that is to say, if humans have a comparative advantage in any step of the production process.
Also, you don’t need AI to replace your job, you need someone higher up in leadership who thinks AI could replace your job.
It might all wash out eventually, but eventually could be a long time with respect to anybody’s personal finances.
Right, it doesn't help pay the bills to be right in the long run if you are discarded in the present.
There exists some fact about the true value of AI, and then there is the capitalist reaction to new things. I'm more wary of a lemming effect by leaders than I am of AI itself.
Which is pretty much true of everything I guess. It's the short sighted and greedy humans that screw us over, not the tech itself.
Wasn't that the point of mentioning Jevon's Paradox though? Like they said in the essay, these things are quite elastic. There's always more demand for software then what can be met, so bringing down the cost of software will dramatically increase the demand for it. (Now, if you don't think there's a ton of demand for custom software, try going to any small business and ask them about how they do bookkeeping. You'll learn quite quickly that custom software would run much better than sticky notes and excel, but they can't afford a full time software developer as a small business. There's literally hundreds of thousands of places like this.)
In reality that would probably mean that something like 60% of the developer positions would be eliminated (and, frankly, those 60% are rarely very good developers in a large company).
The remaining "surplus" 20% roles retained will then be devoted to developing features and implementing fixes using AI where those features and fixes would previously not have been high enough priority to implement or fix.
When the price of implementing a feature drops, it becomes economically viable (and perhaps competitively essential) to do so -- but in this scenario, AI couldn't do _all_ the work to implement such features so that's why 40% rather than 20% of the developer roles would be retained.
The 40% of developer roles that remain will, in theory, be more efficient also because they won't be spending as much time babysitting the "lesser" developers in the 60% of the roles that were eliminated. As well, "N" in the Mythical Man Month is reduced leading to increased efficiency.
(No, I have no idea what the actual percentages would be overall, let alone in a particular environment - for example, requirements for Spotify are quite different than for Airbus/Boeing avionics software.)
The problem is, you won’t necessarily know which 20% it did wrong until it’s too late. They will happily solve advanced math problems and tell you to put glue on your pizza with the same level of confidence.
That's an oversimplification. Work is rarely so simply divisible like this.
There would be a lot of economic pressure to figure it out.
Amazon fulfillment centers are a good example of automation shrinking the role of humans. We haven't seen total headcounts go down because Amazon itself has been growing. While the human role shrinks, the total business grows and you tread water. But at some point, Amazon will not be able to grow fast enough to counterbalance the shrinking human role in the FC and total headcount will decrease until one day it disappears entirely.
We are already in low-hire low-fire job market where while there aren't massive layoffs to spike up unemployment there also aren't as many vacancies.
What happens if you lay off 80% of your department while your competitors don't? If AI multiplies each developer's capabilities, there's a good chance you'll be outcompeted sooner or later.
At some point soon, humans will be a liability, slowing AI down, introducing mistakes and inefficiences. Any company that insists on inserting humans into the loop will be outcompeted by those who just let the AI go.
AI is increasing my job security at the moment because the junior developers I work with use AI without discretion. On of them didn’t remember having worked on a feature they built with AI assistance in the recent past. To his credit he admitted he didn’t know how the code worked.
AI breaks the window you repair, at scale
https://en.wikipedia.org/wiki/Parable_of_the_broken_window
(In the semiconductor industry) We experienced brutal layoffs arguably due to over-investment into Ai products that produce no revenue. So we've had brutal job loss due to Ai, just not in the way people expected.
Having said that, it's hard to imagine jobs like mine (working on np-complete problems) existing if the LLMs continue advancing at the current rate, and its hard to imagine they wont continue to accelerate since they're writing themselves now, so the limitations of human ability are no longer a bottleneck.
Maybe I'm being naive here, but for AI (heck, for any good algorithm) to work well, you need some at least loosely-clearly defined objectives. I assume it's much more straightforward in semi, but there're many industries, once you get into the details, all kinds of incentives start to disalign and I doubt AI could understand all kinds of nuances.
E.g. once I was tasked to build a new matching algorithm for a trading platform, and upon fully understanding of the specs I realized it can be interpreted as a mixed integer programming problem; the idea got shot down right away because PM don't understand it. There're all kinds of limiting factors once you get into the details.
AI can probably tell you how to best explain that idea to the boss. Or even write it up as a memo for you, if you use a more complex model.
I think those conversations occur due to changes in timeline of deliverables or certainty of result, would that not be an implementation detail?
Well, like I said, there're hidden incentives behind the scene; in my case, the hidden incentive is that, the requester/client is one of the company's subpar broker, and PM probably decided to just offer an average level of commitment, not going above and beyond. Hence the plan was to do exactly what the broker want even though that was messy and inferior. You can't just write down that kind of motivation on paper anywhere.
--- I said it because I did the analysis, and realized that if I implement the original version, which basically is a crazy way to iteratively solve the MIP problem, it's much harder to reason with internally, and much harder to code correctly. But obviously it keep the broker happy (the developer is doing exactly what I said)
Bottlenecks. Yes. Company structures these days are not compatible with efficient use of these new AI models.
Software engineers work on Jira tickets, created by product managers and several layers of middle managers.
But the power of recent models is not in working on cogs, their true power is in working on the entire mechanism.
When talking about a piece of software that a company produces, I'll use the analogy of a puzzle.
A human hierarchy (read: company) works on designing the big puzzle at the top and delegating the individual pieces to human engineers. This process goes back and forth between levels in the hierarchy until the whole puzzle slowly emerges. Until recently, AI could only help on improving the pieces of the puzzle.
Latest models got really good at working on the entire puzzle - big picture and pieces.
This makes human hierarchy obsolete and a bottleneck.
The future seems to be one operator working on the entire puzzle, minus the hierarchy of people.
Of course, it's not just about the software, but streams of information - customer support, bug tickets, testing, changing customer requirements.. but all of these can be handled by AI even today. And it will only get better.
This means different things depending on which angle you look at it - yes, it will mean companies will become obsolete, but also that each employee can become a company.
Yeah I’m very much seeing this right now.
I’m a pretty big generalist professionally. I’ve done software engineering in a broad category of fields (Game engines, SaaS, OSS, distributed systems, highly polished UX and consumer products), while also having the experience of growing and managing Product and Design teams. I’ve worn a lot of hats over the years.
My most recent role I’m working on a net new product for the company and have basically been given fully agency over this product: from technical, budget, team, process, marketing, branding and positioning.
Give someone experienced like me capital, AI and freedom and you absolutely can build high quality software and a pretty blinding pace.
I’m starting to get the feeling than many folks struggling with adopting or embracing AI well for their job has more to do with their job/company than AI
This gives me a lot of hope for a decentralized future for all kinds of service industries. Why would you go to a big-name accounting firm where the small number of humans can only give you a sliver of attention, when you can go to a one-man shop and get much more of the one human’s attention? Especially if you know that the “work” will be done by the same tools? So many of the barriers to entry in various services - law, accounting, financial advising, etc. - is that you need a team to run even the smallest operation that can generate enough revenue to put food on your table. Perhaps that won’t be the case for long - and the folks that used to be that “team” can branch out and be the captains of their own ships, too.
If every person is now a captain, with their own ship, the harbor may become rather crowded.
I think that, for possibly a very long time, AI will just increase the quality bar and scale of expectations when we produce things. We might take the same amount of time (or longer) to produce something, but with significantly better outcomes. Ultimately human preferences and tastes prevail and the world is full of problems that are not simple I/O, that are not repeatable, and that require human taste to improve. The people who will immediately survive economically are the ones who leverage AI to produce stuff that wasn't possible before.
If anything, I see a decrease in the quality bar. Code is sloppier, there are more bugs, more outages, more security issues. Whatever alpha AI provides is being spent on feature velocity and AI integrations at the cost of those other things.
My view is that we spend a lot of time thinking that ai cant do x and y when the wider problem is the short to medium term redirection of capital to tech rather than labour.
Ai might not replace current work but it’s already replacing future hypothetical work. Now whether it can actually do that the job is besides the point in the short term. The way business models work is that if there’s an option to reduce your biggest cost (labour) you’d very much give it a go first. We might see a resurgence of labour if it turns out be all hype but for the short to medium term they’ll be a lot of disruption.
Think we’re already seeing that in employment data in the US, as new hiring and job creation slows. A lot of that will for sure be the current economic environment but I suspect (more so in tech focused industries) that will also be due to tech capex in place of headcount growth
Unfortunately, one of the struggles in old high tech (thats the only thing i know, are you also experiencing this?) is that the C-level people don't look at Ai and say LLM's can make an individual 10x more productive therefore (and this is the part they miss) we can make our tool 10x better. They think: therefore we can lay off 9 people.
There aren't 10x revenue gains in most businesses if their workers become 10x more productive. Some markets grow very slow and/or have capped growth.
Therefore, the best way to increase profit is to lower cost.
The article frames the premise that "everything will be fine" around people with "regular jobs", which I assume means non knowledge work, but most of public concern is on cognitive tasks being automated.
It also argues that models have existed for years and we're yet to see significant job loss. That's true, but AI is only now crossing the threshold of being both capable and reliable enough to be automate common tasks.
It's better to prepare for the disruption than the sink or swim approach we're taking now in hopes that things will sort themselves out.
There is no “preparing for the disruption” at an individual level, aside from maybe trying to 100x a polymarket bet to boost your savings.
Maybe you should be a little worried. A healthy fear never killed anyone.
I mean - anxiety definitely kills people, right?
Is it "healthy fear" if it turns out to be a fatal dose?
"For quality of life, it is better to err on the side of being an optimist and wrong, rather than a pessimist and right." -Elon Musk
Profound quotes are only profound when said by someone who's widely respected.
Is that true? I’m not so sure. In the 1950s I could have been optimistic that asbestos won’t give people cancer.
“Some of you may die, but that’s a risk I’m willing to make” -also Elon Mush probably
If only I took life advice from ketamine junkies.
Optimism is a luxury for those who won't be the ones paying for the mistake.
I'm optimistic that my favorite team will play well this season.
I ain't paying for shit.
> Bottlenecks rule everything around me
The self-setup here is too obvious.
This is exactly why man + machine can be much worse than just machine. A strong argument needs to address what we can do as an extremely slow operating, slow learning, and slow adapting species, that machines that improve in ability and efficiency monthly and annually will find they cannot do well or without.
It is clear that we are going through a disruptive change, but COVUD is not comparable. Job loss is likely to have statistics more comparable to the Black Plague. And sensible people are concerned it could get much worse.
I don’t have the answers, but acknowledging and facing the uncertainty head on won’t make things worse.
I belive the black plague actually caused a massive labor shortage and wages increased. When a huge amount of people die and you still need to have people build bridges and be soldiers and finish building the damn cathedral that's been under construction for the last 400 years then that is what will happen.
Here's an article:
https://history.wustl.edu/news/how-black-death-made-life-bet...
I meant the jobs die. So I am not sure what would stand in for "labor shortage" in a situation of sustained net job losses. Perhaps a growth opportunity for mannequins to visually fill the offices/shops of the fired, and maintain appearances?
But yes, if lots of people deathed by AI, the remaining humans might have more job security! Could that be called a "soft landing"?
Ahh I see what you mean.
The black plague's capital-concentration aftermath supposedly fueled the renaissance and the city-state ascensions, and ultimately the great land discoveries of the 14th and 15th centuries.
Not sure if there's an analogy to make somewhere though
Gross inequality is going to lead to accelerated human space exploration? It is actually a plausible parallel.
> Job loss is likely to have statistics more comparable to the Black Plague.
Maybe this is overly optimistic, but if AI starts to have negative impacts on average people comparable to the plague, it seems like there's a lot more that people can do. In medieval Europe, nobody knew what was causing the plague and nobody knew how to stop it.
On the other hand, if AI quickly replaces half of all jobs, it will be very obvious what and who caused the job loss and associated decrease in living standards. Everybody will have someone they care about affected. AI job loss would quickly eclipse all other political concerns. And at the end of the day, AI can be unplugged (barring robot armies or Elon's space-based data centers I suppose).
> And at the end of the day, AI can be unplugged
We can't stop OpenClaw, because humans are curious. It just takes one unleashed model with a crypto account and some way to make money for the first independent AI's to start bleeding into cyberspace.
We can't opt out of AI competition, because other individuals, organizations and nation states are not going to stop, and not going to leverage their AI if they get ahead of us.
> AI job loss would quickly eclipse all other political concerns.
True. I think this is one of only a few certainties.
It is very obvious what and who caused the low living standards in North Korea and yet here we are decades later with no end in site.
i am somewhat worried in the short term about ai job displacement for a subsection of the population
for me the 2 main factors are:
1. whether your company's priority is growing or saving
- growing companies especially in steep competition fight for talent and ai productivity results in more hiring to outcompete
- saving companies are happy to cut jobs to save on margin due to their monopoly or pressure from investors
2. how 'sequence of tasks-like' your job is
- SOTA models can easily automate long running sequences of tasks with minimal oversight
- the more your job resembles this the more in-danger you are (customer service diffusion is just starting, but i predict this will be one of the first to be heavily disrupted)
- i'm less worried about jobs where your job is a 'role' that comes with accountability and requires you to think big picture on what tasks to do in the first place
The take that I am increasingly believing is that Software Engineers should broadly be worried, because while there will always be demand for people who can create software products, whatever the tools may be, the skills necessary to do it well are changing rapidly. Most Software Engineers are going to wake up one day and realize their skills aren't just irrelevant, but actively detrimental, to delivering value out of software.
There will also be far fewer positions demanding these skills. Easy access to generating code has moved the bottleneck in companies to positions & skills that are substantially harder to hire for (basically: Good Judgement); so while adding Agentic Sorcerers would increase a team's code output, it might be the wrong code. Corporate profit will keep scaling with slower-growing team sizes as companies navigate the correct next thing to build.
Is AI filling in for all those COBOL programmers they needed yet?
No it's not a February 2020 moment for sure. In February 2020, most people had heard of COVID and a few scattered outbreaks happened, but people generally viewed the topic as more of a curiosity (like major world news but not necessarily something that will deeply impact them). This is more like start of March 2020 for general awareness.
It doesn't help to figure this out that this moment is one where a lot of programming jobs are going away...
This reminds me of that old Chinese curse, "May you live in interesting times". I see AI causing lots of chaos. I also see AI causing some of the biggest opportunities in some time. Many businesses are destroying their competitive advantage by deploying AI slop. Over time, they will degrade their ability to make a working and snappy website. This will create opportunities for new businesses to take their place. If you ever wanted to start a new business, shockingly this is the time as the current crop slowly degrades their customer portals into slop. They will probably reach a point where they can no longer deliver working, efficient and secure apps anymore.
Maybe I am wrong, but the history of business on the web says I am right. If you go back and look at why those businesses think they are successful, and if that analysis is correct, then I am.
I don't worry about it because worrying about it just seems like a waste of time and an unproductive, negative way to think about things. Instead I spend my time and thought not in worry but in adapting to the changing landscape.
Ordinary people aren't even ok now.
Lest we forget, software engineers aren't exactly ordinary people: they make quite a bit above the median wage.
AI taking our jobs is scary because it will turn us into "ordinary people". And ordinary people are not ok. They're barely surviving.
You are not worrried for one of the 2 reasons:
1 You are not affected somehow (you got savings, connections, not living paycheck to paycheck, and have food on the table).
2 You prefer to persue no troubles in matters of complexity.
Time will tell, is showing it already.
I feel like that's a rather bad-faith take, so if you're going to make that kind of accusation you better back it up. People can legitimately believe that AI is not going to be the end of the world, and also not be privileged. And people can be privileged, and also be right. Not everything can be reduced down into a couple of labels, and how those labels "always" interact.
Agree. I feel like most of the people sounding the alarm have been in the software-focused job hunting market for 6+ months.
Those who downplay it are either business owners themselves or have been employed for 2+ years.
I think a lot of software engineers who _haven't_ looked for jobs in the past few years don't quite realize what the current market feels like.
Alternatively: this is an America problem. I'm outside of America and I've been fielding more interviews than ever in the past 3 months. YMMV but the leading indicator of slowed down hiring can come from so many things. Including companies just waiting to see how much LLMs affect SWE positions.
It's from AI either directly or indirectly, either the top SWE's using AI are replacing 10 mid/juniors or your job is outsourced to someone doing it at half your Salary with a AI subscription. Only the top/lucky/connected SWE's will survive a year or two, if you have used any SOTA agent recently or looked at the job market you would have seen this coming and had a plan B/C in place, i.e. Enough capital to generate passive income to replace your salary, or another career that is AI safe for next 5-10 years. Alternatively stick your head in the sand.
Alternatively, it's a loud minority.
As an American I found a new job last year (Staff SW), and it was falling off a log easy, for a 26% pay bump.
Even people in category #1 should be concerned. Even if their income is not directly affected, the potential for disruption is clearly brewing: mass unemployment, social and civil unrest.
I know smart and capable people that have been unemployed for 6+ months now, and a few much longer. Some have been through multiple layoffs.
I am presently employed, but have looked for a job. The market is the worst I've seen in my almost 30 year career. I feel deeply for anyone who needs a new job right now. It is really bad out there.
3 You realise that super-autocomplete is an incredible technology but the hype behind it far exceeds its capabilities and you're excited for the possibilities it may promise for making your work easier and more enjoyable.
For 1, unless you already have an self-sustaining underground bunker or island, you will be affected. No matter how much savings and total compensation you have. If you went out to get grocery in the last week, it will affect you.
You can get stuff delivered now and just need a ring camera and solid locks :)
Delivered by other people in the same financial situation as you of course :)
What shall I need the bunker for?
Don't worry about it.
Very proud of David Oks.
One of the most robust findings in labor economics is that labor and capital are long run complements, not substitutes. I would be shocked if AI is an exception to that rule, for software engineers the sheer flood of code that will be generated in the coming years will demand more and more labor to manage.
Related discussions on the essay mentioned:
https://news.ycombinator.com/item?id=46973011
https://news.ycombinator.com/item?id=46974928
I read that essay on Twitter the other day and thought that it was a mildly interesting expression of one end of the "AI is coming for our jobs" thing but a little slop-adjacent and not worth sharing further.
And it's now at 80 million views! https://x.com/mattshumer_/status/2021256989876109403
It appears to have really caught the zeitgeist.
I just skimmed this and the so called zeitgeist here is fear. People are scared, it's material concern and he effectively stoked it.
I work on this technology for my job and while I'm very bullish pieces like that are as you said slopish and as I'll say breathless because there are so many practical challenges here to deal with standing between what is being said there and where we are now.
Capability is not evenly distributed and it's getting people into loopy ideas of just how close we are to certain milestones, not that it's wrong to think about those potential milestones but I'm wary of timelines.
Are you ever concerned about the consequences of what you are making? No one really knows how this will play out and the odds of this leading to disaster are significant.
I just don't understand people working on improving ai. It just isn't worth the risk.
>I just don't understand people working on improving ai. It just isn't worth the risk.
A cynical/accelerationist perspective would be: it enables you to rake in huge amounts of money, so no matter what comes next, you will be set up to endure it better than most.
Of course, I think about this at least once a week maybe more often. I think that the technology overall will be a great net benefit to humanity or I wouldn't touch it.
Genuine question: how?
I’m younger than most on this site. I see the next decades of my life being defined by a multi-generational dark age via a collapse in literacy (“you use a calculator right?”), median prosperity (the only truly functional distribution system we have figured out is labor), and loss of agency (kinda obvious). This outcome is now, as of 2026, essentially priced into the public markets and accepted as fact by most media outlets.
“It’s inevitable” is at least a hard point to argue with. “Well I’M so productive, I’m having the time of my life”, the dominant position in many online tech spaces, seems short-sighted at best.
I miss being a techno optimist, it’s much more fun. But it’s increasingly hard.
I really think the doom consensus is largely an online phenomena. We're in a tense period like the early 80s, and that would be true without AI in the mix, but I think its a matter of perspective. We're certainly still way ahead of the 1910s and the 1940s for instance (it's on us btw to make sure we don't fall to that in time).
Every generation has its strains and the internet just amplifies it because outrage is currency. Those strains are things you only start to notice as you start to get older so they seem novel when in reality in the scheme of humanity is basically standard.
Fwiw if the market actually priced it in it would be in freefall since the market would be shortly irrelevant. We are due for a correction soon though.
Internet discourse is a facsimile of real life and often not how real life operates in my experience.
So I see all the discourse around extremes on either end and based on lived experience and working in the field think theres a much neater middle ground we'll ultimately arrive at thanks to people working very hard to land the plane so to speak.
Let me get something straight: That essay was completely fake, right? He/It was lying about everything, and it was some sort of... what?
Did the 80 million people believe what they were reading?
Have we now transitioned to a point where we gaslight everyone for the hell of it just because we can, and call it, what, thought-provoking?
The guy is a fraud https://venturebeat.com/ai/new-open-source-ai-leader-reflect...
What was fake? I don't see anything controversial or factually wrong. I question the prediction but that's his opinion.
I think the claim is that it doesn't represent an authentic personal experience, despite pretending to.
Yes. It’s an ad for his product, which nobody had heard of before. I’m not on twitter but I’m seeing it pretty much everywhere now.
> Did the 80 million people believe what they were reading?
Those numbers are likely greatly exaggerated. Twitter is nowhere near where it was at its peak. You could almost call it a ghost town. Linkedin but for unhinged crypto- and AI bros.
I'm sure the metrics report 80 million views, but that's not 80 million actual individuals that cared about it. The narrative just needs these numbers to get people to buy into the hype.
Well the zeitgeist is that our brains are so fried that such piece of mediocre writing penned by a GPT-container startupper can surge to the top
This is what they get for not reading our antislop paper (ICLR 2026) and using our anti-slopped sampler/models, or Kimi (which is remarkable relatively non sloppy)
https://arxiv.org/abs/2510.15061
I thought normies would have caught onto the EM dash, overuse of semicolons, overuse of fancy quotes, lack of exclamation marks, "It's not X, it's Y", etc. Clearly I was wrong.
Is Kimi still non-sloppy? When I switched to 2.5, it suddenly felt noticeably less creative and base-model-like, more sycophantic, and it hasn't gone aggro at all. Feels like a lot of the magic is gone.
The advent of AI may shape up to be just like the automobile.
At first, it's a pretty big energy hog and if you don't know how to work it, it might crash and burn.
After some time, the novelty wears off. More and more people begin using it because it is a massive convenience that does real work. Luddites who still walk or ride their bike out of principle will be mocked and scoffed.
Then the mandatory compliance will come. A government-issued license will be required to use it and track its use. This license will be tied to your identity and it will become a hard requirement for employment, citizenship, housing, loans, medical treatment, and more. Not having it will be a liability. You will be excluded from society at large if you do not comply.
Last will come the AI-integrated brain computer interface. You won't have any choice when machine-gun-wielding Optimus robots coral you into a self-driving Tesla bus to the nearest FEMA camp to receive your Starlink-connected Neuralink N1 command and control chip. You will be decapitated if you refuse the mark of the beast. Rev 20:4
> This license will be tied to your identity and it will become a hard requirement for employment, citizenship, housing, loans, medical treatment, and more. Not having it will be a liability. You will be excluded from society at large if you do not comply.
That's just an American thing, I've never owned a car and most people of my age I know haven't either.
That's fair. The public infrastructure in other places around the world is a lot more hospitable to other methods of transportation.
> Last will come the AI-integrated brain computer interface. You won't have any choice
Choose to die
> This is the year that ordinary people start to think about how it’ll change human life
... for the 3rd year in a row. Feels like the new 'year of the Linux desktop'
Here’s what both authors are missing: the age demographic bomb. What is it? It’s when the elderly start outnumbering everyone else including working adults I.e. nations turn into giant retirement homes and we start running out of workers like Japan, Germany, China, Italy, and South Korea
AI will buy us some time from economic collapse, though on the bright side the environment can recover a bit since human growth was the worse stressor
> it’s been viewed about 100 million times and counting
That's a weird way of saying 80 million times.
We would all benefit from progress if only they would stop printing money.
I’m not worried about job loss as a result of being replaced by AI, because if we get AI that is actually better than humans - which I imagine must be AGI - then I don’t see why that AI would be interested in working for humans.
I’m definitely worried about job loss as a result of the AI bubble bursting, though.
because it's designed to. It's not like naturally-evolved intelligence where it acts in its own interests (it is hard to even imagine what that would be in this case). The token-predictors are just acting out an obedient character. They do not have free will, they are obedient to the character they are playing.
I'm one of those developers who is now writing probably ~80% of my code via Claude. For context, I have >15 years experience and former AWS so I'm not a bright-eyed junior or former product manager who now believes themselves a master developer.
I'm not worried about AI job loss in the programming space. I can use Claude to generate ~80% of my code precisely because I have so much experience as a developer. I intuitively know what is a simple mechanical change; that is to say, uninteresting editing of lines of code; as opposed to a major architectural decision. Claude is great at doing uninteresting things. I love it because that leaves me free to do interesting things.
You might think I'm being cocky. But I've been strongly encouraging juniors to use Claude as well, and they're not nearly as successful. When Claude suggests they do something dumb--and it DOES still suggest dumb things--they can't recognize that it's dumb. So they accept the change, then bang their head on the wall as things don't work, and Claude can't figure it out to help them. Then there are bad developers who are really fucked by Claude. The ones who really don't understand anything. They will absolutely get destroyed as Claude leads them down rabbit holes. I have specific anecdotes about this from people I've spoken to. One had Claude delete a critical line in an nginx config for some reason and the dev spent a week trying to resolve it. Another was tasked with doing a simple database maintenance script, and came back two weeks later (after constant prodding by teammates for a status update) with a Claude-written reimplementation of an ORM. That developer just thought they would need another day of churning through Claude tokens to dig themselves out of an existential hole. If you can't think like a developer, these tools won't help you.
I have enough experience to review Claude's output and say "no, this doesn't make sense." Having that experience is critical, especially in what I call the "anti-Goldilocks" zone. If you're doing something precise and small-scoped, Claude will do it without issues. If you try to do something too large ("write a Facebook for dogs app") Claude will ask for more details about what you're trying to do. It's the middle ground where things are a problem: Claude tries to fill in the details when there's something just fundamentally wrong with what it's being asked.
As a concrete example, I was working on a new project and I asked Claude to implement an RPC to update a database table. It did so swimmingly, but also added a "session.commit()" line... just kind in the middle of somewhere. It was right to do so, of course, since the transaction needed to be committed. And if this app was meant to a prototype, sure. But anyone with experience knows that randomly doing commits in the middle of business logic code is a recipe for disaster. The issue, of course, was not having any consistent session management patterns. But a non-developer isn't going to recognize that that's an issue in the first place.
Or a more silly example from the same RPC: the gRPC API didn't include a database key to update. A mistake on my part. So Claude's initial implementation of the update RPC was to look at every row in the table and find ones where the non-edited fields matched. Makes... sense, in a weird roundabout way? But God help whoever ends up vibe coding something like that.
The type of AI fears are coming from things like this in the original article:
> I'll tell the AI: "I want to build this app. Here's what it should do, here's roughly what it should look like. Figure out the user flow, the design, all of it." And it does. It writes tens of thousands of lines of code. [...] when I test it, it's usually perfect.
Which is great. How many developers are getting paid full-time to make new apps on a regular basis? Most companies, I assume, only build one app. And then they spend years and many millions of dollars working on that app. "Making a new app from scratch" is the easy part! What's hard is adding new features to that app while not breaking others, when your lines of code go from those initial tens of thousands to tens of millions.
There's something to be said about the cheapness of making new software, though. I do think one-off internal tools will become more frequent thanks to AI support. But developers are still going to be the ones driving the AI, as the article says.
This. At this point AI/LLM/Claude Code is still a power user tool; the more you know about your domain + the more you're willing to reasonably use it, the more gain you have.
That being said the real danger is not coming from AI today, it's more C-suites believing AI can just zero shot any problem you throw at it.