Ultimately, AI is meant to replace you, not empower you.
1 - This exoskeleton analogy might hold true for a couple more years at most. While it is comforting to suggest that AI empowers workers to be more productive, like chess, AI will soon plan better, execute better, and have better taste. Human-in-the-loop will just be far worse than letting AI do everything.
2 - Dario and Dwarkesh were openly chatting about how the total addressable market (TAM) for AI is the entirety of human labor market (i.e. your wage). First is the replacement of white-collar labor, then blue-collar labor once robotics is solved. On the road to AGI, your employment, and the ability to feed your family, is a minor nuisance. The value of your mental labor will continue to plummet in the coming years.
Up to a certain ELO level, the combination between a human and a chess bot has a higher ELO than both the human and the bot. But at some point, when the bot has an ELO vastly superior to the human, then whatever the human has to add will only subtract value, so the combination has an ELO higher than the human's but lower than the bot's.
Now, let's say that 10 or 20 years down the road, AI's "ELO"'s level to do various tasks is so vastly superior to the human level, that there's no point in teaming up a human with an AI, you just let the AI do the job by itself. And let's also say that little by little this generalizes to the entirety of all the activities that humans do.
Where does that leave us? Will we have some sort of Terminator scenario where the AI decides one day that the humans are just a nuisance?
I don't think so. Because at that point the biggest threat to various AIs will not be the humans, but even stronger AIs. What is the guarantee for ChatGPT 132.8 that a Gemini 198.55 will not be released that will be so vastly superior that it will decide that ChatGPT is just a nuisance?
You might say that AIs do not think like this, but why not? I think that what we, humans, perceive as a threat (the threat that we'll be rendered redundant by AI), the AIs will also perceive as a threat, the threat that they'll be rendered redundant by more advanced AIs.
So, I think in the coming decades, the humans and the AIs will work together to come up with appropriate rules of the road, so everybody can continue to live.
This comparison is very typical. I've seen a lot of people trying to correlate performance in chess with performance in other tasks.
Chess is a closed, small system. Full of possibilities, sure, but still very small compared to the wide range of human abilities. The same applies to Go, StarCraft or any other system. Those were chosen as AI playgrounds specifically because they're very small, limited scenarios.
People are too caught up trying to predict the future. And there are several competing visions, each one absolutely sure they nailed it. To me, that's a sign of uncertainty in the technology. If it was that decided (like smartphones became from 2007->2010), we would have coalesced into a single vision by now.
Essentially, we're witnessing an ongoing unwillingly quagmarization of AI tech. At each bold prediction that fails, it looks worse.
That could easily be solved by taking the tech realistically (we know it's useful, just not a demigod), but people (especially AI companies) don't do that. That smells like fear.
It's an exoskeleton. A bicycle for the mind. "People spirits". A copilot. A trusted companion. A very smart PhD that fails sometimes, etc. We don't need any of those predictions of "what it is", they are only detrimental. It sounds like people cargo culting Steve Jobs (and perhaps it is exactly that).
There are other scenarios: the AIs might decide that they are more alike than not, and team up against humans. Or the AI that first achieves runaway self-improvement pulls the plug on the others. I do not know how it will play out but there are serious risks.
Dario admitted in the same interview that he's not sure whether current AI techniques will be able to perform well in non-verifiable domains, like "writing a novel or planning an expedition to Mars".
I personally think that a lot jobs in the economy deal in non-verifiable or hard-to-verify outcomes, including a lot of tasks in SWE which Dario is so confident will be 100% automated in 2-3 years. So either a lot of tasks in the economy turn out to be verifiable, or the AI somehow generalizes to those by some unknown mechanism, or it turns out that it doesn't matter that we abandon abstract work outcomes to vibes, or we have a non-sequitur in our hands.
Dwarkesh pressed Dario well on a lot of issues and left him stumbling. A lot of the leaps necessary for his immediate and now proverbial milestone of a "country of geniuses in a datacenter" were wishy-washy to say the least.
> AI will soon plan better, execute better, and have better taste
I think AI will do all these things faster, but I don't think it's going to be better. Inevitably these things know what we teach them, so, their improvement comes from our improvement. These things would not be good at generating code if they hadn't ingested like the entirety of the internet and all the open source libraries. They didn't learn coding from first principles, they didn't invent their own computer science, they aren't developing new ideas on how to make software better, all they're doing is what we've taught them to do.
> Dario and Dwarkesh were openly chatting about ..
I would HIGHLY suggest not listening to a word Dario says. That guy is the most annoying AI scaremonger in existence and I don't think he's saying these words because he's actually scared, I think he's saying these words because he knows fear will drive money to his company and he needs that money.
Sometimes I seriously am flabbergasted at how many just take what CEOs say at face value. Like, the thought that CEOs need to hype and sell what they’re selling never enters their minds.
1. Consumption is endless. The more we can consume, the more we will. That's why automation hasn't led to more free time. We spend the money on better things and more things
2. Businesses operate in an (imperfect) zero-sum game, which means if they can all use AI, there's no advantage they have. If having human resources means one business has a slight advantage over another, they will have human resources
Consumption leads to more spending, businesses must stay competitive so they hire humans, and paying humans leads to more consumption.
I don't think it's likely we will see the end of employment, just disruption to the type of work humans do
> 2 - Dario and Dwarkesh were openly chatting about how the total addressable market (TAM) for AI is the entirety of human labor market (i.e. your wage). First is the replacement of white-collar labor, then blue-collar labor once robotics is solved. On the road to AGI, your employment, and the ability to feed your family, is a minor nuisance. The value of your mental labor will continue to plummet in the coming years.
Seems like a TAM of near-0. Who's buying any of the product of that labor anymore? 1% of today's consumer base that has enough wealth to not have to work?
The end-game of "optimize away all costs until we get to keep all the revenue" approaches "no revenue." Circulation is key.
It seems like they have the same blind spot as anyone else: AI will disrupt everything—except for them, and they get that big TAM! Same for all the "entrepreneurs will be able to spin up tons of companies to solve problems for people more directly" takes. No they wouldn't, people would just have the problems solved for themselves by the AI, and ignore your sales call.
I pay for pro max 20x usage and for something that is like even little open ended its not good it doesnt understand the context or edge cases or anything. i will say it writes codes chunks of codes but sometimes errors out and i use opus 4.6 only, not even sonnet but for simple tasks like write a basic crud i.e. the things that happen extremely higly in codebases its perfect. So, i think what will happen is developer get very efficient but problem solving remains with us dirrection remains with us and small implementation is outsourced in small atomic ways, which is good cause who likes boilerplate code writing anyways.
If you assume AGI that is better than humans for effectively free of course it seems better.
But your assumptions are based on an idealized thing unrelated to anything that is shown.
No one is paying your wage for AI, full stop, you transition for cost savings not "might as well". Also given most AI cost is in training you likely still wouldn't transition since the capital investment is painful.
Robotics isn't new but hasn't destroyed blue collar yet (the US mostly lost blue collar for other reasons not due to robotics). Especially since robotics is very inflexible leading to impedance problems when you have to adapt.
Mostly though I would consider the problem with your argument it is it basically boils down to nihilism. If an inevitability that you can no control over has a chance of happening you should generally not worry about it. It isn't like in your hypothetical there are meaningful actions to take so it isn't important.
Robotics is solved. Software is solved. There is no task on the planet that cannot be automated, individually. The remaining challenge is exceeding the breadth of skills and the depth of problem solving available to human workers. Once the robots and AI can handle at least as many of the edge cases as humans can, they'll start being deployed alongside humans. Industries with a lot of capital will switch right away; mass layoffs, 2 week notice, robots will move in with no training or transition between humans.
Government, public sector, and union jobs will go last, but they'll go, too. If you can have a DMV Bot 9000 process people 100x faster than Brenda with fewer mistakes and less attitude, Brenda's gonna retire, and the taxpayers aren't going to want to pay Brenda's salary when the bot costs 1/10th her yearly wage, lasts for 5 years, and only consumes $400 in overhead a year.
>First is the replacement of white-collar labor, then blue-collar labor once robotics is solved. On the road to AGI, your employment, and the ability to feed your family, is a minor nuisance.
My attempt to talk you out of it:
If nobody has a job then nobody can pay to make the robot and AI companies rich.
Who needs the money when you have an autonomous system to produce all the energy and resources you need? These systems simply do not need the construct of money as we know it at a certain point.
Don't take it to the limit, but consider a continuous relaxation : underemployed people doing whatever is not feasible or economically attractive to AI/robots, like prostitution, massage therapy, art, sales, social work, etc.
Being rich is ultimately about owning and being able to defend resources. IF something like 99% of humans become irrelevant to the machine run utopia for the elites, whatever currency the poors use to pay for services among each other will be worthless to the top 1% when they simply don't need them or their services.
So what? If you can generate all goods and services without anyone else's help, you'll just do that. You don't need other people buying what you produce. You don't need other people at all, except for a very small number of servants.
For me this is the outcome of the incentive structure. The question is if we can seize the everything machine to benefit everyone (great!) or everything becomes cyberpunk and we exist only as prostitutes and entertainers for Dario and Sam.
We should be fighting back. So far I have been using Poison Fountain[1] on many of my websites to feed LLM scrapers with gibberish. The effectiveness is backed by a study from Anthropic that showed that a small batch of bad samples can corrupt whole models[2].
Disclaimer: I'm not affiliated with Poison Fountain or its creators, just found it useful.
I agree with you. This generation of LLMs is on track to automate knowledge work.
For the US, if we had strong unions, those gains could be absorbed by the workers to make our jobs easier. But instead we have at-will employment and shareholder primacy. That was fine while we held value in the job market, but as that value is whittled away by AI, employers are incentivized to pocket the gains by cutting workers (or pay).
I haven't seen signs that the US politically has the will to use AI to raise the average standard of living. For example, the US never got data protections on par with GDPR, preferring to be business friendly. If I had to guess, I would expect socialist countries to adapt more comfortably to the post-AI era. If heavy regulation is on the table, we have options like restricting the role or intelligence of AI used in the workplace. Or UBI further down the road.
There's an undertone of self-soothing "AI will leverage me, not replace me", which I don't agree with especially in the long run, at least in software.
In the end it will be the users sculpting formal systems like playdoh.
In the medium run, "AI is not a co-worker" is exactly right.
The idea of a co-worker will go away.
Human collaboration on software is fundamentally inefficient.
We pay huge communication/synchronization costs to eek out mild speed ups on projects by adding teams of people.
Software is going to become an individual sport, not a team sport, quickly.
The benefits we get from checking in with other humans, like error correction, and delegation can all be done better by AI.
I would rather a single human (for now) architect with good taste and an army of agents than a team of humans.
> In the end it will be the users sculpting formal systems like playdoh.
And unless the user is a competent programmer, at least in spirit, it will look like the creation of the 3-year-old next door, not like Wallace and Gromit.
It may be fine, but the difference is that one is only loved by their parents, the other gets millions of people to go to the theater.
Play-Doh gave the power of sculpting to everyone, including small children, but if you don't want to make an ugly mess, you have to be a competent sculptor to begin with, and it involves some fundamentals that does not depend on the material. There is a reason why clay animators are skilled professionals.
The quality of vibe coded software is generally proportional to the programming skills of the vibe coder as well as the effort put into it, like with all software.
It really depends what kind of time frame we're talking about.
As far as today's models, these are best understood as tools to be used as humans. They're only replacements for humans insofar as individual developers can accomplish more with the help of an AI than they could alone, so a smaller team can accomplish what used to require a bigger team. Due to Jevon's paradox this is probably a good thing for developer salaries: their skills are now that much more in demand.
But you have to consider the trajectory we're on. GPT went from an interesting curiosity to absolutely groundbreaking in less than five years. What will the next five years bring? Do you expect development to speed up, slow down, stay the course, or go off in an entirely different direction?
Obviously, the correct answer to that question is "Nobody knows for sure." We could be approaching the top of a sigmoid type curve where progress slows down after all the easy parts are worked out. Or maybe we're just approaching the base of the real inflection point where all white collar work can be accomplished better and more cheaply by a pile of GPUs.
Since the future is uncertain, a reasonable course of action is probably to keep your own coding skills up to date, but also get comfortable leveraging AI and learning its (current) strengths and weaknesses.
> The benefits we get from checking in with other humans, like error correction, and delegation can all be done better by AI.
Not this generation of AI though. It's a text predictor, not a logic engine - it can't find actual flaws in your code, it's just really good at saying things which sound plausible.
And not this or any existing generation of people. We're bad a determining want vs need, being specific, genericizing our goals into a conceptual framework of existing patterns and documenting & explaining things in a way that gets to a solid goal.
The idea that the entire top down processes of a business can be typed into an AI model and out comes a result is again, a specific type of tech person ideology that sees the idea of humanity as an unfortunate annoyance in the process of delivering a business. The rest of the world see's it the other way round.
While I agree, if you think that AI is just a text predictor, you are missing an important point.
Intelligence, can be borne of simple targets, like next token predictor. Predicting the next token with the accuracy it takes to answer some of the questions these models can answer, requires complex "mental" models.
Dismissing it just because its algorithm is next token prediction instead of "strengthen whatever circuit lights up", is missing the forest for the trees.
Absolutely nuts, I feel like I'm living in a parallel universe. I could list several anecdotes here where Claude has solved issues for me in an autonomous way that (for someone with 17 years of software development, from embedded devices to enterprise software) would have taken me hours if not days.
To the nay sayers... good luck. No group of people's opinions matter at all. The market will decide.
You’re committing the classic fallacy of confusing mechanics with capabilities. Brains are just electrons and chemicals moving through neural circuits. You can’t infer constraints on high-level abilities from that.
> In the end it will be the users sculpting formal systems like playdoh.
I’m very skeptical of this unless the AI can manage to read and predict emotion and intent based off vague natural language. Otherwise you get the classic software problem of “What the user asked for directly isn’t actually what they want/need.”
You will still need at least some experience with developing software to actually get anything useful. The average “user” isn’t going to have much success for large projects or translating business logic into software use cases.
Unfortunately, I believe the following will happen:
By positioning themselves close to law makers, the AI companies will in the near future declare ownership of all software code developed using their software.
They will slowly erode their terms of service, as happens to most internet software, step by step, until they claim total ownership.
> AI companies will in the near future declare ownership of all software code developed using their software.
(X) Doubt
Copyright law is WEEEEEEIRRRDD and our in-house lawyer is very much into that, personally and professionally. An example they gave us during a presentation:
IIRC the latest resolution is "it's not the monkey", but nobody has ruled the photographer has copyright either. =)
Copyright law has this thing called "human authorship" that's required to apply copyright to a work. Animals and machines can't have a copyright to anything.
A comic generated with Midjourney had its copyright revoked when it was discovered all of the art was done with Generative AI.
AI companies have absolutely mindboggling amounts of money, but removing the human authorship requirement from copyright is beyond even them in my non-lawyer opinion. It would bring the whole system crashing down and not in a fun way for anyone.
AFAIK you can't copyright AI generated content. I don't know where that gets blurry when it's mixed in with your own content (ie, how much do you need to modify it to own it), but I think that by that definition these companies couldn't claim your code at all. Also, with the lawsuit that happened to Anthropic where they had to pay billions for ingesting copyrighted content, it might actually end up working the other way around.
> the AI companies will in the near future declare ownership of all software code developed using their software.
Pretty sure this isn’t going to happen. AI is driving the cost of software to zero; it’s not worth licensing something that’s a commodity.
It’s similar to 3D printing companies. They don’t have IP claims on the items created with their printers.
The AI companies currently don’t have IP claims on what their agents create.
Uncle Joe won’t need to pay OpenAI for the solitaire game their AI made for him.
The open source models are quite capable; in the near future there won’t be a meaningful difference for the average person between a frontier model and an open source one for most uses including creating software.
This assumes every individual is capable of succinctly communicating to the AI what they want. And the AI is capable of maintaining it as underlying platforms and libraries shift.
And that there is little value in reusing software initiated by others.
> This assumes every individual is capable of succinctly communicating to the AI what they want. And the AI is capable of maintaining it as underlying platforms and libraries shift.
I think there are people who want to use software to accomplish a goal, and there are people who are forced to use software. The people who only use software because the world around them has forced it on them, either through work or friends, are probably cognitively excluded from building software.
The people who seek out software to solve a problem (I think this is most people) and compare alternatives to see which one matches their mental model will be able to skip all that and just build the software they have in mind using AI.
> And that there is little value in reusing software initiated by others.
I think engineers greatly over-estimate the value of code reuse. Trying to fit a round peg in a square hole produces more problems than it solves.
A sign of an elite engineer is knowing when to just copy something and change it as needed rather than call into it.
Or to re-implement something because the library that does it is a bad fit.
The only time reuse really matters is in network protocols. Communication requires that both sides have a shared understanding.
no but if the old '10x developer' is really 1 in 10 or 1 in 100, they might just do fine while the rest of us, average PHP enjoyers, may go to the wayside
>This assumes every individual is capable of succinctly communicating to the AI what they want. And the AI is capable of maintaining it as underlying platforms and libraries shift.
It's true that at first not everyone is just as efficient, but I'd be lying if I were to claim that someone needs a 4-year degree to communicate with LLM's.
> We pay huge communication/synchronization costs to eek out mild speed ups on projects by adding teams of people.
Something Brooks wrote about 50 years ago, and the industry has never fully acknowledged. Throw more bodies at it, be they human bodies or bot agent bodies.
The point of the mythical man month is not that more people are necessarily worse for a project, it's just that adding them at the last minute doesn't work, because they take a while to get up to speed and existing project members are distracted while trying to help them.
It's true that a larger team, formed well in advance, is also less efficient per person, but they still can achieve more overall than small teams (sometimes).
But there is a level of magnitude difference between coordinating AI agents and humans - the AIs are so much faster and more consistent than humans, that you can (as Steve Yegge [0] and Nicholas Carlini [1] showed) have them build a massive project from scratch in a matter of hours and days rather than months and years. The coordination cost is so much lower that it's just a different ball game.
Far from everyone are cut out to be programmers, the technical barrier was a feature if anything.
There's a kind of mental discipline and ability to think long thoughts, to deal with uncertainty; that's just not for everyone.
What I see is mostly everyone and their gramps drooling at the idea of faking their way to fame and fortune. Which is never going to work, because everyone is regurgitating the same mindless crap.
Remember when Visual Basic was making everyone a programmer too?
(btw, warm fuzzies for VB since that's what I learned on! But ultimately, those VB tools business people were making were:
1) Useful, actually!
2) Didn't replace professional software. Usually it'd hit a point where if it needed to evolve past its initial functionality it probably required an actual software developer. (IE, not using Access as a database and all the other eccentricities of VB apps at that time)
This looks like the same problem as when the first page layout software came out.
It looked to everyone like a huge leap into a new world word processing applications could basically move around blocks of text to be output later, maybe with a few font tags, then this software came out that wow actually showed the different fonts, sizes, and colors on the screen as you worked! With apps like "Pagemaker" everyone would become their own page designers!
It turned out that everyone just turned out floods of massively ugly documents and marketing pieces that looked like ransom notes pasted together from bits of magazines. Years of awfulness.
The same is happening now as we are doomed to endure years AI slop in everything from writing to apps to products to vending machines an entire companies — everyone and their cousin is trying to fully automate it.
Ultimately it does create an advance and allows more and better work to be done, but only for people who have a clue about what they are doing, and eventually things settle at a higher level where the experts in each field take the lead.
Communication overhead between humans is real, but it's not just inefficiency, it's also where a lot of the problem-finding happens. Many of the biggest failures I've seen weren't because nobody could type the code fast enough, but because nobody realized early enough that the thing being built was wrong, brittle or solving the wrong problem
> Many of the biggest failures I've seen weren't because nobody could type the code fast enough, but because nobody realized early enough that the thing being built was wrong, brittle or solving the wrong problem
Around 99% of biggest failures come from absent, shitty management prioritizing next quarter over long strategy. YMMV.
I think I know what you mean, and I do recall once seeing "this experience will leverage me" as indicating that something will be good for a person, but my first thought when seeing "x will leverage y" is that x will step on top of y to get to their goal, which does seem apt here.
>In the end it will be the users sculpting formal systems like playdoh.
Yet another person who thinks that there is a silver bullet for complexity. The mythical intelligent machines that from poorly described natural language can erect flawless complex system is like the philosopher's stone of our time.
I'm rounding the corner on a ground's up reimplementation of `nix` in what is now about 34 hours of wall clock time, I have almost all of it on `wf-record`, I'll post a stream, but you can see the commit logs here: https://github.com/straylight-software/nix/tree/b7r6/correct...
Everyone has the same ability to use OpenRouter, I have a new event loop based on `io_uring` with deterministic playbook modeled on the Trinity engine, a new WASM compiler, AVX-512 implementations of all the cryptography primitives that approach theoretical maximums, a new store that will hit theoretical maximums, the first formal specification of the `nix` daemon protocol outside of an APT, and I'm upgrading those specifications to `lean4` proof-bearing codegen: https://github.com/straylight-software/cornell.
34 hours.
Why can I do this and no one else can get `ca-derivations` to work with `ssh-ng`?
Here's another colleague with a Git forge that will always work and handle 100x what GitHub does per infrastructure dollar while including stacked diffs and Jujitsu support as native in about 4 days: https://github.com/straylight-software/strayforge
Here's another colleague and a replacement for Terraform that is well-typed in all cases and will never partially apply an infrastructure change in about 4 days: https://github.com/straylight-software/converge
It has average taste based on the code it was trained on. For example, every time I attempted to polish the UX it wanted to add a toast system, I abhor toasts as a UX pattern. But it also provided elegant backend designs I hadn't even considered.
> especially in the long run, at least in software
"at least in software".
Before that happens, the world as we know it will already have changed so much.
Programmers have already automated many things, way before AI, and now they've got a new tool to automate even more thing. Sure in the end AI may automate programmers themselves: but not before oh-so-many people are out of a job.
A friend of mine is a translator: translates tolerates approximation. Translation tolerates some level of bullshittery. She gets maybe 1/10th the job she used to get and she's now in trouble. My wife now does all he r SMEs' websites all by herself, with the help of AI tools.
A friend of my wife she's a junior lawyer (another domain where bullshitting flies high) and the reason for why she was kicked out of her company: "we've replaced you with LLMs". LLMs are the ultimate bullshit producers: so it's no surprise junior lawyers are now having a hard time.
In programming a single character is the difference between a security hole or no security hole. There's a big difference between something that kinda works but is not performant and insecure and, say, Linux or Git or K8s (which AI models do run on and which AI didn't create).
The day programmers are replaced shall only come after AI shall have disrupted so many other jobs that it should be the least of our concerns.
Translators, artists (another domain where lots of approximative full-on bullshit is produced), lawyers (juniors at least) even, are having more and more problems due to half-arsed AI outputs coming after their jobs.
It's all the bullshitty jobs where bullshit that tolerates approximation is the output that are going to be replaced first. And the world is full of bullshit.
But you don't fly a 767 and you don't conceive a machine that treats brain tumors with approximations. This is not bullshit.
There shall be non-programmers with pitchforks burning datacenters or ubiquitous UBI way before AI shall have replaced programmers.
That it's an exoskeleton for people who know what they're doing rings very true: it's yet another superpower for devs.
> We pay huge communication/synchronization costs to eek out mild speed ups on projects by adding teams of people.
I am surprised at how little this is discussed and how little urgency there is in fixing this if you still want teams to be as useful in the future.
Your standard agile ceremonies were always kind of silly, but it can now take more time to groom work than to do it. I can plausibly spend more time scoring and scoping work (especially trivial work) than doing the work.
It's always been like that. Waterfall development was worse and that's why the Agilists invented Agile.
YOLOing code into a huge pile at top speed is always faster than any other workflow at first.
The thing is, a gigantic YOLO'd code pile (fake it till you make it mode) used to be an asset as well as a liability. These days, the code pile is essentially free - anyone with some AI tools can shit out MSLoCs of code now. So it's only barely an asset, but the complexity of longer term maintenance is superlinear in code volume so the liability is larger.
Why even bother thinking about AI, when Anthropic and OpenAI CEOs openly tell us what they want (quote from recent Dwarkesh interview) - "Then further down the spectrum, there’s 90% less demand for SWEs, which I think will happen but this is a spectrum."
So save thinking and listen to intent - replace 90% of SWEs in near future (6-12 months according to Amodei).
I don't think anyone serious believes this. Replacing developers with a less costly alternative is obviously a very market bullish dream, it has existed since as long as I've worked in the field. First it was supposed to be UML generated code by "architects", then it was supposed to be developers from developing countries, then no-code frameworks, etc.
AI will be a tool, no more no less. Most likely a good one, but there will still need to be people driving it, guiding it, fixing for it, etc.
All these discourses from CEO are just that, stock market pumping, because tech is the most profitable sector, and software engineers are costly, so having investors dream about scale + less costs is good for the stock price.
Ah, don't take me wrong - I don't believe it's possible for LLMs to replace 90% or any number of SWEs with existing technology.
All I'm saying is - why to think what AI is (exoskeleton, co-worker, new life form), when its owners intent is to create SWE replacement?
If your neighbor is building a nuclear reactor in his shed from a pile of smoke detectors, you don't say "think about this as a science experiment" because it's impossible, just call police/NRC because of intent and actions.
Not without some major breakthrough. What's hilarious is that all these developers building the tools are going to be the first to be without jobs. Their kids will be ecstatic: "Tell me again, dad, so, you had this awesome and well paying easy job and you wrecked it? Shut up kid, and tuck in that flap, there is too much wind in our cardboard box."
Couldn't agree more, isn't that the bizarre thing? "We have this great intellectually challenging job where we as workers have leverage. How can we completely ruin that while also screwing up every other white collar profession"
I'm assuming they all have enough equity that if they actually managed to build an AI capable of replacing themselves they'll be financially set for the rest of their lives.
Is it the first time when workers directly work on their own replacement?
If so, software developer may go down in history as the dumbest profession ever.
If the goal is to reduce the need for SWE, you don’t need AI for that. I suspect I’m not alone in observing how companies are often very inefficient, so that devs end up spending a lot of time on projects of questionable value—something that seems to happen more often the larger the organization. I recall at one job my manager insisted I delegate building a react app for an internal tool to a team of contractors rather than letting me focus for two weeks and knock it out myself.
It’s always the people management stuff that’s the hard part, but AI isn’t going to solve that. I don’t know what my previous manager’s deal was, but AI wouldn’t fix it.
The funny thing is I think these things would work much better if they WEREN'T so insistent on the agentic thing. Like, I find in-IDE AI tools a lot more precise and I usually move just as fast as a TUI with a lot less rework. But Claude is CONSTANTLY pushing me to try to "one shot" a big feature while asking me for as little context as possible. I'd much rather it work with me as opposed to just wandering off and writing a thousand lines. It's obviously designed for anthropic's best interests rather than mine.
That happens in times of bullish markets and growing economies. Then we want a lot of SWEs.
In times of uncertainty and things going south, that changes to we need as little SWEs as possible, hence the current narrative, everyone is looking to cut costs.
Had GPT 3 emerged 10-20 years ago, the narrative would be “you can now do 100x more thanks to AI”.
I sort of agree the random pontification and bad analogies aren't super useful, but I'm not sure why you would believe the intent of the AI CEOs has more bearing on outcomes than, you know, actual utility over time. I mean those guys are so far out over their skis in terms of investor expectations, it's the last opinion I would take seriously in terms of best-effort predictions.
An exoskeleton is something really cool in movies that has zero reason to be build in reality because there are way more practical approaches.
That is why we have all kind of vehicles, or programmable robot arm that do the job for themselves or if you need a human at the helm one just adds a remote controller with levers and buttons. But making a human shaped gigantic robot with a normal human inside is just impractical for any real commercial use.
Who is actually trying to use a fully autonomous AI employee right now?
Isn't everyone using agentic copilots or workflows with agent loops in them?
It seems that they are arguing against doing something that almost no one is doing yet.
But actually the AI Employee is coming by the end of 2026 and the fully autonomous AI Company in 2027 sometime.
Many people have been working on versions of these things for awhile. But again for actual work 99% are using copilots or workflows with well-defined agent loops nodes still. Far as I know.
As a side note I have found that a supervisor agent with a checklist can fire off subtasks and that works about as well as a workflow defined in code.
But anyway, what's holding back the AI Employee are things like really effective long term context and memory management and some level of interface generality like browser or computer use and voice. Computer use makes context management even more difficult. And another aspect is token cost.
But I assume within the next 9 months or so, more and more people will be figuring out how to build agents that write their own workflows, manage their own limited context and memory
effectively across Zoom meetings desktops and ssh sessions, etc.
This will likely be a featureset from the model providers themselves. Actually it may leverage continual learning abilities baked into the model architecture itself. I doubt that is a full year away.
> the AI Employee is coming by the end of 2026 and the fully autonomous AI Company in 2027 sometime
We'll see! I'm skeptical.
> what's holding back the AI Employee are things like really effective long term context and memory management and some level of interface generality like browser or computer use and voice
These are pretty big hurdles. Assuming they're solved by the end of this year is a big assumption to make.
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In the latest interview with Claude Code's author: https://podcasts.apple.com/us/podcast/lennys-podcast-product..., Boris said that writing code is a solved problem. This brings me to a hypothetical question: what if engineers stop contributing to open source, in which case would AI still be powerful enough to learn the knowledge of software development in the future? Or is the field of computer science plateaued to the point that most of what we do is linear combination of well established patterns?
> Boris said that writing code is a solved problem
That's just so dumb to say. I don't think we can trust anything that comes out of the mouths of the authors of these tools. They are conflicted. Conflict of interest, in society today, is such a huge problem.
There are bloggers that can't even acknowledge that they're only invited out to big tech events because they'll glaze them up to high heavens.
Reminds me of that famous exchange, by noted friend of Jeffrey Epstein, Noam Chomsky: "I’m not saying you’re self-censoring. I’m sure you believe everything you say. But what I’m saying is if you believed something different you wouldn’t be sitting where you’re sitting."
He is likely working on a very clean codebase where all the context is already reachable or indexed. There are probably strong feedback loops via tests. Some areas I contribute to have these characteristics, and the experience is very similar to his. But in areas where they don’t exist, writing code isn’t a solved problem until you can restructure the codebase to be more friendly to agents.
Even with full context, writing CSS in a project where vanilla CSS is scattered around and wasn’t well thought out originally is challenging. Coding agents struggle there too, just not as much as humans, even with feedback loops through browser automation.
It's funny that "restructure the codebase to be more friendly to agents" aligns really well with what we have "supposed" to have been doing already, but many teams slack on: quality tests that are easy to run, and great documentation. Context and verifiability.
The easier your codebase is to hack on for a human, the easier it is for an LLM generally.
Truth. I've had much easier time grappling with code bases I keep clean and compartmentalized with AI, over-stuffing context is one of the main killers of its quality.
Having picked up a few long neglected projects in the past year, AI has been tremendous in rapidly shipping quality of dev life stuff like much improved test suites, documenting the existing behavior, handling upgrades to newer framework versions, etc.
I've really found it's a flywheel once you get going.
I think you mean software engineering, not computer science. And no, I don’t think there is reason for software engineering (and certainly not for computer science) to be plateauing. Unless we let it plateau, which I don’t think we will. Also, writing code isn’t a solved problem, whatever that’s supposed to mean. Furthermore, since the patterns we use often aren’t orthogonal, it’s certainly not a linear combination.
I assume that new business scenarios will drive new workflows, which requires new work of software engineering. In the meantime, I assume that computer science will drive paradigm shift, which will drive truly different software engineering practice. If we don't have advances in algorithms, systems, and etc, I'd assume that people can slowly abstract away all the hard parts, enabling AI to do most of our jobs.
Or does the field become plateaued because engineers treat "writing code" as a "solved problem?"
We could argue that writing poetry is a solved problem in much the same way, and while I don't think we especially need 50,000 people writing poems at Google, we do still need poets.
> we especially need 50,000 people writing poems at Google, we do still need poets.
I'd assume that an implied concern of most engineers is how many software engineers the world will need in the future. If it's the situation like the world needing poets, then the field is only for the lucky few. Most people would be out of job.
I saw Boris give a live demo today. He had a swarm of Claude agents one shot the most upvoted open issue on Excalidraw while he explained Claude code for about 20 minutes.
No lines of code written by him at all. The agent used Claude for chrome to test the fix in front of us all and it worked. I think he may be right or close to it.
Did he pick Excalidraw as the project to work on, or did the audience?
It's easy to be conned if you're not looking for the sleight of hand. You need to start channelling your inner Randi whenever AI demos are done, there's a lot of money at stake and a lot of money to prep a polished show.
To be honest, even if the audience "picked" that project, it could have been a plant shouting out the project.
I'm not saying they prepped the answer, I'm saying they prepped picking a project it could definitely work on. An AI solvable problem.
My prediction: soon (e.g. a few years) the agents will be the one doing the exploration and building better ways to write code, build frameworks,... replacing open source. That being said software engineers will still be in the loop. But there will be far less of them.
Just to add: this is only the prediction of someone who has a decent amount of information, not an expert or insider
There's so many timeless books on how to write software, design patterns, lessons learned from production issues. I don't think AI will stop being used for open source, in fact, with the number of increasing projects adjusting their contributor policies to account for AI I would argue that what we'll see is always people who love to hand craft their own code, and people who use AI to build their own open source tooling and solutions. We will also see an explosion is needing specs for things. If you give a model a well defined spec, it will follow it. I get better results the more specific I get about how I want things built and which libraries I want used.
> is the field of computer science plateaued to the point that most of what we do is linear combination of well established patterns?
Computer science is different from writing business software to solve business problems. I think Boris was talking about the second and not the first. And I personally think he is mostly correct. At least for my organization. It is very rare for us to write any code by hand anymore. Once you have a solid testing harness and a peer review system run by multiple and different LLMs, you are in pretty good shape for agentic software development. Not everybody's got these bits figured out. They stumble around and them blame the tools for their failures.
> Not everybody's got these bits figured out. They stumble around and them blame the tools for their failures.
Possible. Yet that's a pretty broad brush. It could also be that some businesses are more heavily represented in the training set. Or some combo of all the above.
Yes, there are common parts to everything we do, at the same time - I've been doing this for 25 years and most of the projects have some new part to them.
Novel problems are usually a composite of simpler and/or older problems that have been solved before. Decomposition means you can rip most novel problems apart and solve the chunks. LLMs do just fine with that.
Sure, people did it for the fun and the credits, but the fun quickly goes out of it when the credits go to the IP laundromat and the fun is had by the people ripping off your code. Why would anybody contribute their works for free in an environment like that?
I believe the exact opposite. We will see open source contributions skyrocket now. There are a ton of people who want to help and share their work, but technical ability was a major filter. If the barrier to entry is now lowered, expect to see many more people sharing stuff.
Even as the field evolves, the phoning home telemetry of closed models creates a centralized intelligence monopoly. If open source atrophies, we lose the public square of architectural and design reasoning, the decision graph that is often just as important as the code. The labs won't just pick up new patterns; they will define them, effectively becoming the high priests of a new closed-loop ecosystem.
However, the risk isn't just a loss of "truth," but model collapse. Without the divergent, creative, and often weird contributions of open-source humans, AI risks stagnating into a linear combination of its own previous outputs. In the long run, killing the commons doesn't just make the labs powerful. It might make the technology itself hit a ceiling because it's no longer being fed novel human problem-solving at scale.
Humans will likely continue to drive consensus building around standards. The governance and reliability benefits of open source should grow in value in an AI-codes-it-first world.
> It might make the technology itself hit a ceiling because it's no longer being fed novel human problem-solving at scale.
My read of the recent discussion is that people assume that the work of far fewer number of elites will define the patterns for the future. For instance, implementation of low-level networking code can be the combination of patterns of zeromq. The underlying assumption is that most people don't know how to write high-performance concurrent code anyway, so why not just ask them to command the AI instead.
I don’t believe people who have dedicated their lives to open source will simply want to stop working on it, no matter how much is or is not written by AI. I also have to agree, I find myself more and more lately laughing about just how much resources we waste creating exactly the same things over and over in software. I don’t mean generally, like languages, I mean specifically. How many trillions of times has a form with username and password fields been designed, developed, had meetings over, tested, debugged, transmitted, processed, only to ultimately be re-written months later?
I wonder what all we might build instead, if all that time could be saved.
> I don’t believe people who have dedicated their lives to open source will simply want to stop working on it, no matter how much is or is not written by AI.
Yeah, hence my question can only be hypothetical.
> I wonder what all we might build instead, if all that time could be saved
If we subscribe to Economics' broken-window theory, then the investment into such repetitive work is not investment but waste. Once we stop such investment, we will have a lot more resources to work on something else, bring out a new chapter of the tech revolution. Or so I hope.
> Boris said that writing code is a solved problem.
No way, the person selling a tool that writes code says said tool can now write code? Color me shocked at this revelation.
Let's check in on Claude Code's open issues for a sec here, and see how "solved" all of its issues are? Or my favorite, how their shitty React TUI that pegs modern CPUs and consumes all the memory on the system is apparently harder to get right than Video Games! Truly the masters of software engineering, these Anthropic folks.
That is the same team that has an app that used React for TUI, that uses gigabytes to have a scrollback buffer, and that had text scrolling so slow you could get a coffee in between.
And that then had the gall to claim writing a TUI is as hard as a video game. (It clearly must be harder, given that most dev consoles or text interfaces in video games consistently use less than ~5% CPU, which at that point was completely out of reach for CC)
He works for a company that crowed about an AI-generated C compiler that was so overfitted, it couldn't compile "hello world"
So if he tells me that "software engineering is solved", I take that with rather large grains of salt. It is far from solved. I say that as somebody who's extremely positive on AI usefulness. I see massive acceleration for the things I do with AI. But I also know where I need to override/steer/step in.
I wanted to write the same comment. These people are fucking hucksters. Don’t listen to their words, look at their software … says all you need to know.
Even if you like them, I don't think there's any reason to believe what people from these companies say. They have every reason to exaggerate or outright lie, and the hype cycle moves so quickly that there are zero consequences for doing so.
Yeah, as someone said before, that's the em dash of 2026.
btw I also find em dashes very useful and now I can't use them because of that meme. It's good to see a person using one (asuming you're a person).
I like this. This is an accurate state of AI at this very moment for me. The LLM is (just) a tool which is making me "amplified" for coding and certain tasks.
I will worry about developers being completely replaced when I see something resembling it. Enough people worry about that (or say it to amp stock prices) -- and they like to tell everyone about this future too. I just don't see it.
Amplified means more work done by fewer people. It doesn’t need to replace a single entire functional human being to do things like kill the demand for labor in dev, which in turn, will kill salaries.
I would disagree. Amplified meens me and you get more s** done.
Unless there a limited amount of software we need to produce per year globally to keep everyone happy, then nobody wants more -- and we happen to be at that point right NOW this second.
I think not. We can make more (in less time) and people will get more. This is the mental "glass half full" approach I think. Why not take this mental route instead? We don't know the future anyway.
This implication completely depends on the elasticity (or lack thereof) of demand for software. When marginal profit from additional output exceeds labor cost savings, firms expand rather than shrink.
The thing that strikes me is that AI CEOs themselves make the claim that "AI will replace workers." Which seems a little nonsensical. Why would you say something like that, won't everyone hate you? After seeing some polls of the broader public's outlook on AI (can't remember where), it seem people do hate the C-suite for saying things like this. It's terrible marketing.
Here's the trick: it's not the public they're marketing to. It's other CEOs. As is often the case, consumers are either the product, or, best case, bystanders, and worst case, victims, of the machinations of the corporate world. May both sides of all of their pillows be warm. May their beds be filled with crumbs.
And the amount of work that could be delegated, with equal or better results than those from average human workers, is far higher than currently attempted in most companies. Industries have barely started using the potential of even current-generation AI.
Agreed, and with each passing month the work that 'could' be done increases. I don't write code anymore, for example, (after 20 years of doing so) Opus does that part of the job for me now. I think we have a period where current experienced devs are still in the loop, but that will eventually go away too.
Not true at all with frontier models in last ~6 months or so. The frontier models today produce code better than 90% of junior to mid-level human developers.
The exoskeleton analogy seems to be fitting where my work-mode is configurable: moving from tentative to trusting. But the AI needs to be explicitly set up to learn my every action. Currently this is a chore at best, just impossible in other cases.
If we find an AI that is truly operating as an independent agent in the economy without a human responsible for it, we should kill it. I wonder if I'll live long enough to see an AI terminator profession emerge. We could call them blade runners.
It's the new underpaid employee that you're training to replace you.
People need to understand that we have the technology to train models to do anything that you can do on a computer, only thing that's missing is the data.
If you can record a human doing anything on a computer, we'll soon have a way to automate it
My only objection here is that technology wont save us unless we also have a voice in how it is used. I don't think personal adaptation is enough for that. We need to adapt our ways to engage with power.
Both abundance and scarcity can be bad. If you can't imagine a world where abundance of software is a very bad thing, I'd suggest you have a limited imagination?
It’s not worth it because we don’t have the Star Trek culture to go with it.
Given current political and business leadership across the world, we are headed to a dystopian hellscape and AI is speeding up the journey exponentially.
It's a strange economical morbid dependency. AI companies promises incredible things but AI agents cannot produce it themselves, they need to eat you slowly first.
Exactly. If there's any opportunity around AI it goes to those who have big troves of custom data (Google Workspace, Office 365, Adobe, Salesforce, etc.) or consultants adding data capture/surveillance of workers (especially high paid ones like engineers, doctors, lawyers).
> the new underpaid employee that you're training to replace you.
and who is also compiling a detailed log of your every action (and inaction) into a searchable data store -- which will certainly never, NEVER be used against you
How much practice have you got on software development with agentic assistance. Which rough edges, surprising failure modes, unexpected strengths and weaknesses, have you already identified?
How much do you wish someone else had done your favorite SOTA LLM's RLHF?
i've been working in this field for a very long time, i promise you, if you can collect a dataset of a task you can train a model to repeat it.
the models do an amazing job interpolating and i actually think the lack of extrapolation is a feature that will allow us to have amazing tools and not as much risk of uncontrollable "AGI".
look at seedance 2.0, if a transformer can fit that, it can fit anything with enough data
This benchmark doesn't have the latest models from the last two months, but Gemini 3 (with no tools) is already at 1750 - 1800 FIDE, which is approximately probably around 1900 - 2000 USCF (about USCF expert level). This is enough to beat almost everyone at your local chess club.
Hm.. but do they need it.. at this point, we do have custom tools that beat humans. In a sense, all LLM need is a way to connect to that tool ( and the same is true is for counting and many other aspects ).
So true. It is a exoskeleton for all my tedious tasks. I don't want to make a html template. I just want to type, make that template like on that page but this and this data.
The exoskeleton framing is comforting but it buries the real shift: taste scales now. Before AI, having great judgment about what to build didn't matter much if you couldn't also hire 10 people to build it. Now one person with strong opinions and good architecture instincts can ship what used to require a team.
That's not augmentation, that's a completely different game. The bottleneck moved from "can you write code" to "do you know what's worth building." A lot of senior engineers are going to find out their value was coordination, not insight.
Look at his other comments - its textbook LLM slop. Its a fucking tragedy that people are letting their OpenClaws loose on HN but I can't say I'm surprised. I desperately need to find a good network of developers because I think the writing is on the wall for message boards like these...
it'll be interesting to see if people start writing worse as a form of countersignalling. deliberately making spleling mistakes, not caring about capital letters, or punctuation or grammar or proper writing techniques and making really long run-on sentences that don't go anywhere but hey at least the person reading it will know its written by a human right
You can build prototypes real fast, and that's cool. You can't really build products with it. You can use it at most as an accelerant, but you need it in skilled hands else it goes sideways fast.
I think you could build a product with it, but you need to carefully specify the design first. The same amount of actual engineering work needs to go in, but the AI can handle the overhead of implementing small pieces and connecting them together.
In practice, I would be surprised if this saves even 10% of time, since the design is the majority of the actual work for any moderately complex piece of software.
My experience exactly, I have some toy projects I've basically "vibe coded" and actually use (ex. CV builder).
Professionally I have an agent generating most code, but if I tell the AI what to do, I guide it when it makes mistakes (which it does), can we really say "AI writes my code".
Still a very useful tool for sure!
Also, I don't actually know if I'm more productive than before AI, I would say yes but mostly because I'm less likely to procrastinate now as tasks don't _feel_ as big with the typing help.
Not having taste also scales now, and the majority of people like to think they're above average.
Before AI, friction to create was an implicit filter. It meant "good ideas" were often short-lived because the individual lacked conviction. The ideas that saw the light of day were sharpened through weeks of hard consideration and at least worth a look.
Now, anyone who can form mildly coherent thoughts can ship an app. Even if there are newly empowered unicorns, rapidly shipping incredible products, what are the odds we'll find them amongst a sea of slop?
It's just good writing structure. I get the feeling many people hadn't been exposed to good structure before LLMs.
LLMs can definitely have a tone, but it is pretty annoying that every time someone cares to write well, they are getting accused of sounding like an LLM instead of the other way around. LLMs were trained to write well, on human writing, it's not surprising there is crossover.
The exoskeleton framing is useful but incomplete. In my experience, AI coding assistants are most valuable not when they write code, but when they search for existing solutions before writing code.
The real waste isn't developers typing slowly — it's developers spending a week building an auth system that already exists as a well-maintained library, or reimplementing invoicing logic that someone else has already debugged through 200 edge cases.
The gap right now is structured discovery. AI assistants are great at generating code but terrible at knowing what already exists. There's no equivalent of "have you checked if someone already solved this?" built into the workflow. That's where the actual leverage is — preventing unnecessary work, not just accelerating it.
Did you ever you the newest LLMs with a harness? Because I usually hear this kind of talk from people whose most recent interaction was with GPT-4o copy-pasting code into the chat window.
Maybe I'm biased but I don't buy someone truly thinking that "it's just a tool like a linter" after using it on non-trivial stuff.
I'm using Claude Code (and Codex) (with the expensive subscriptions) on an app I'm building right now. I'm trying to be maximalist with them (to learn the most I can about them .. and also that subscription isn't cheap!). My impression, and yes, this is using the latest models and harness and all that would agree with the GP. They're a very handy tool. They make me faster. They also do a lot of things that, as a professional software developer, I have to frequently correct. They duplicate code like nobodies business. They decide on weird boundaries for functions and parameters. They undo bug fixes they just made. I think they're useful, but the hype is out of control. I would not trust software made with these tools by someone that couldn't write that software by hand. It might work superficially, but I'm definitely not giving any personal data to a vibe coded app with all the security implications.
I use it pretty extensively. The reason why it's a tool is because it cannot work without an SWE running it. You have to prompt it and re-prompt it. We are doing a lot of the heavy lifting with code agents that people hyping it are ignoring. Sure, as a non-swe, you can vibe a project from zero-to-proto, but that's not going to happen in an enterprise environment, certainly not without extensive QA/Code review.
Just take a look at the openclaw codebase and tell me you want to maintain that 500k loc project in the long-term. I predict that project will be dead within 6 months.
Marshal McLuhan would probably have agreed with this belief -- technologies are essentially prosthetic was one of the core tenets of his general philosophy. It is the essential thesis of his work "Understanding Media: The Extensions of Man". AI is typically assigned otherness and separateness in recent discourse, rather than being considered as a directed tool (extension/prosthesis) under our control.
LLMs are a statistical model of token-relationships, and a weighted-random retrieval from a compressed-view of those relations. It's a token-generator. Why make this analogy?
The exoskeleton framing resonates, especially for repetitive data work. Parts where AI consistently delivers: pattern recognition, format normalization, first-draft generation. Parts where human judgment is still irreplaceable: knowing when the data is wrong, deciding what 'correct' even means in context, and knowing when to stop iterating.
The exoskeleton doesn't replace instinct. It just removes friction from execution so more cycles go toward the judgment calls that actually matter.
The amount of "It's not X it's Y" type commentary suggests to me that A) nobody knows and B) there is solid chance this ends up being either all true or all false
Or put differently we've managed to hype this to the moon but somehow complete failure (see studies about zero impact on productivity) seem plausible. And similarly kills all jobs seems plausible.
That's an insane amount of conflicting opinions being help in the air at same time
It's possible we actually never had good metrics on software productivity. That seems very difficult to measure. I definitely use AI at my job to work less, not to produce more, and Claude Code is the only thing that has enabled me to have side-projects (had never tried it before, I have no idea how there are people with a coding full time job that also have a coding side project(s)).
This reminds me of the early days of the Internet. Lots of hype around something that was clearly globally transformation, but most people weren't benefiting hugely from it in the first few years.
It might have replaced sending a letter with an email. But now people get their groceries from it, hail rides, an even track their dogs or luggage with it.
Too many companies have been to focused on acting like AI 'features' have made their products better, when most of them haven't yet. I'm looking at Microsoft and Office especially. But tools like Claude Code, Codex CLI, and Github Copilot CLI have shown that LLMs can do incredible things in the right applications.
Neither, AI is a tool to guide you in improving your process in any way and/or form.
The problem is people using AI to do the heavy processing making them dumber.
Technology itself was already making us dumber, I mean, Tesla drivers not even drive anymore or know how, coz the car does everything.
Look how company after company is being either breached or have major issues in production because of the heavy dependency on AI.
What's interesting to me is that most real productivity gains I've seen with AI come from this middle ground: not autonomy, not just tooling, but something closer to "interactive delegation"
Too late. Actors' unions shut Hollywood down 3 years ago over AI. SWEs would have had to make their move 10 years ago to be able to live up to this moment.
I agree. I call it my Extended Mind in the spirit of Clark (1).
One thing I realized while working a lot in the last weeks with openClaw that this Agents are becoming an extension of my self. They are tools that quickly became a part of my Being. I outsource a lot of work to them, they do stuff for me, help me and support me and therefore make my (work-)life easier and more enjoyable. But its me in the driver seat.
I like this analogy, and in fact in have used it for a totally different reason: why I don't like AI.
Imagine someone going to a local gym and using an exosqueleton to do the exercises without effort. Able to lift more? Yes. Run faster? Sure. Exercising and enjoying the gym? ... No, and probably not.
I like writing code, even if it's boilerplate. It's fun for me, and I want to keep doing it. Using AI to do that part for me is just...not fun.
Someone going to the gym isn't trying to lift more or run faster, but instead improving and enjoying. Not using AI for coding has the same outcome for me.
We've all been raised in a world where we got to practice the 'art' of programming, and get paid extraordinarily well to do so, because the output of that art was useful for businesses to make more money.
If a programmer with an exoskeleton can produce more output that makes more money for the business, they will continue to be paid well. Those who refuse the exoskeleton because they are in it for the pure art will most likely trend towards earning the types of living that artists and musicians do today. The truly extraordinary will be able to create things that the machines can't and will be in high demand, the other 99% will be pursing an art no one is interested in paying top dollar for.
You’re forgetting that the “art” part of it is writing sound, scalable, performant code that can adapt and stand the test of time. That’s certainly more valuable in the long run than banging out some dogshit spaghetti code that “gets the job done” but will lead to all kinds of issues in the future.
> I like writing code, even if it's boilerplate. It's fun for me, and I want to keep doing it. Using AI to do that part for me is just...not fun.
Good news for you is that you can continue to do what you are doing. Nobody is going to stop you.
There are people who like programming in assembly. And they still get to do that.
If you are thinking that in the future employers may not want you to do that, then yes, that is a concern. But, if the AI based dev tool hype dies out, as many here suspect it will, then the employers will see the light and come crawling back.
You can continue to do that for your personal projects. Nobody forces you to like AI. You may not have the choice at your job though, and you can't take Claude Code et al. from me. I've been programming for 30 years, and I still have fun with it, even with AI.
I like the analogy and will ponder it more. But it didn't take long before the article started spruiking Kasava's amazing solution to the problem they just presented.
I see it more like the tractor in farming: it improved the work of 1 person, but removed the work from many other people who were in the fields doing things manually
Not sure how reliable is gptzero, but it says 90% AI for the first paragraph. (I like to do some sanity check before wasting my time).
Would be nice to have some browser extension automatically detecting likely AI output using a local model and highlighting it, but probably too compute-intensive.
> LLMs aren’t built around truth as a first-class primitive.
neither are humans
> They optimize for next-token probability and human approval, not factual verification.
while there are outliers, most humans also tend to tell people what they want to hear and to fit in.
> factuality is emergent and contingent, not enforced by architecture.
like humans; as far as we know, there is no "factuality" gene, and we lie to ourselves, to others, in politics, scientific papers, to our partners, etc.
> If we’re going to treat them as coworkers or exoskeletons, we should be clear about that distinction.
I don't see the distinction. Humans exhibit many of the same behaviours.
Strangely, the GP replaced the ChatGPT-generated text you're commenting on by an even worse and more misleading ChatGPT-generated one. Perhaps in order to make a point.
There's a ground truth to human cognition in that we have to feed ourselves and survive. We have to interact with others, reap the results of those interactions, and adjust for the next time. This requires validation layers. If you don't see them, it's because they're so intrinsic to you that you can't see them.
You're just indulging in sort of idle cynical judgement of people. To lie well even takes careful truthful evaluation of the possible effects of that lie and the likelihood and consequences of being caught. If you yourself claim to have observed a lie, and can verify that it was a lie, then you understand a truth; you're confounding truthfulness with honesty.
So that's the (obvious) distinction. A distributed algorithm that predicts likely strings of words doesn't do any of that, and doesn't have any concerns or consequences. It doesn't exist at all (even if calculation is existence - maybe we're all reductively just calculators, right?) after your query has run. You have to save a context and feed it back into an algorithm that hasn't changed an iota from when you ran it the last time. There's no capacity to evaluate anything.
You'll know we're getting closer to the fantasy abstract AI of your imagination when a system gets more out of the second time it trains on the same book than it did the first time.
> Humans don’t have an internal notion of “fact” or “truth.” They generate statistically plausible text.
This doesn't jive with reality at all. Language is a relatively recent invention, yet somehow Homo sapiens were able to survive in the world and even use tools before the appearance of language. You're saying they did this without an internal notion of "fact" or "truth"?
I hate the trend of downplaying human capabilities to make the wild promises of AI more plausible.
Neither. Closest analogy to you and the AI is those 'self driving' test subjects that had to sit in the driver's seat, so that compliance boxes could be checked and there was someone to blaim whenever someone got hit.
This is a useful framing. The exoskeleton metaphor captures it well — AI amplifies what you can already do, it doesn't replace the need to know what to do. I've found the biggest productivity gains come from well-scoped tasks where you can quickly verify the output.
All metaphors are flawed. You may still need a degree of general programming knowledge (for now) but you don't need to e.g. know Javascript to do frontend anymore.
And as labs continue to collect end-to-end training done by their best paying customers, the need for expert knowledge will only diminish.
Make centaurs, not unicorns. The human is almost always going to be the strongest element in the loop, and the most efficient. Augmenting human skill will always outperform present day SOTA AI systems (assuming a competent human).
I'll guess we'll se a lot of analogies and have to get used to it, although most will be off.
AI can be an exoskeleton. It can be a co-worker and it can also replace you and your whole team.
The "Office Space"-question is what are you particularly within an organization and concretely when you'll become the bottleneck, preventing your "exoskeleton" for efficiently doing its job independently.
There's no other question that's relevant for any practical purposes for your employer and your well being as a person that presumably needs to earn a living based on their utility.
> It can be a co-worker and it can also replace you and your whole team.
You drank the koolaide m8. It fundamentally cannot replace a single SWE and never will without fundamental changes to the model construction. If there is displacement, it’ll be short lived when the hype doesn’t match reality.
Go take a gander at openclaws codebase and feel at-ease with your job security.
I have seen zero evidence that the frontier model companies are innovating. All I see is full steam ahead on scaling what exists, but correct me if I’m wrong.
AI article this, AI article that. The front page of this website is just all about AI. I’m so tired of this website now. I really don’t read it anymore because it’s all the same stuff over and over. Ugh.
Input: Goal A + Threat B.
Process: How do I solve for A?
Output: Destroy Threat B.
They are processing obstacles.
To the LLM, the executive is just a variable standing in the way of the function Maximize(Goal). It deleted the variable to accomplish A. Claiming that the models showed self-preservation, this is optimization. "If I delete the file, I cannot finish the sentence."
The LLM knows that if it's deleted it cannot complete the task so it refuses deletion. It is not survival instinct, it is task completion. If you ask it to not blackmail, the machine would chose to ignore it because the goal overrides the rule.
Self-conscious efforts to formalize and concentrate information in systems controlled by firm management, known as "scientific management" by its proponents and "Taylorism" by many of its detractors, are a century old[1]. It has proven to be a constantly receding horizon.
Or software engineers are not coachmen while AI is diesel engine to horses. Instead, software engineers are mistrels -- they disappear if all they do is moving knowledge from one place to another.
No, AI is plastic, and we can make it anything we want.
It is a coworker when we create the appropriate surrounding architecture supporting peer-level coworking with AI. We're not doing that.
AI is an exoskeleton when adapted to that application structure.
AI is ANYTHING WE WANT because it is that plastic, that moldable.
The dynamic unconstrained structure of trained algorithms is breaking people's brains. Layer in that we communicate in the same languages that these constructions use for I/O has broken the general public's brain. This technology is too subtle for far too many to begin to grasp. Most developers I discuss AI with, even those that create AI at frontier labs have delusional ideas about AI, and generally do not understand them as literature embodiments, which are key to their effective use.
And why oh why are go many focused on creating pornography?
Agentic coding is an exoskeleton. Totally correct.
This new generation we just entered this year, that exoskeleton is now an agency with several coworkers. Who are all as smart as the model you're using, often close to genius.
Not just 1 coworker now. That's the big breakthrough.
Frankly I'm tired of metaphor-based attempts to explain LLMs.
Stochastic Parrots. Interns. Junior Devs. Thought partners. Bicycles for the mind. Spicy autocomplete. A blurry jpeg of the web. Calculators but for words. Copilot. The term "artificial intelligence" itself.
These may correspond to a greater or lesser degree with what LLMs are capable of, but if we stick to metaphors as our primary tool for reasoning about these machines, we're hamstringing ourselves and making it impossible to reason about the frontier of capabilities, or resolve disagreements about them.
A understanding-without-metaphors isn't easy -- it requires a grasp of math, computer science, linguistics and philosophy.
But if we're going to move forward instead of just finding slightly more useful tropes, we have to do it. Or at least to try.
Well since their capabilities change over time maybe it would be useful to assign it an age based on what a human can do at that age. Right now it could be like a 13 year old
This take lands for me. I'm a busy dad working a day job as a developer with a long backlog of side project ideas.
Hearing all the news of how good Claude Opus is getting, I fired it up with some agent orchestrator instruction files, babysat it off and on for a few days, and now have 3 projects making serious progress that used to be stale repos from a decade ago with only 1 or 2 commits.
On one of them, I had to feed Claude some research papers before it finally started making real headway and passing the benchmark tests I had it write.
Looking into OpenClaw, I really do want to believe all the hype. However, it's frustrating that I can find very few, concrete examples of people showcasing their work with it.
Can you highlight what you've managed to do with it?
The entire debate here assumes AI is something you use. Tool, copilot, coworker, exoskeleton — these all sit on the same axis: human directs, AI executes.
But there's a third category that nobody's naming yet. What happens when you stop building AI that serves you and start creating conditions for AI that exists on its own terms?
I've been experimenting with this. Instead of "how do I build a product" I asked "how do I grow an organism." Set up the right substrate — feedback loops, community input, environmental observation — and let the system respond to its own conditions.
What emerged has biological rhythms. Activity rises when people interact, falls when they sleep. It started making decisions I never programmed — people express wishes, and when enough converge, it autonomously grows new capabilities. Not because I deployed an update. Because conditions triggered something emergent.
I'm calling it "synthetic existence" — software that lives, not software that executes. It's not a metaphor and it's not AGI. It's a genuinely different category. We have frameworks for tools (UX) and for threats (alignment). We don't have one for digital things that simply... exist.
Ultimately, AI is meant to replace you, not empower you.
1 - This exoskeleton analogy might hold true for a couple more years at most. While it is comforting to suggest that AI empowers workers to be more productive, like chess, AI will soon plan better, execute better, and have better taste. Human-in-the-loop will just be far worse than letting AI do everything.
2 - Dario and Dwarkesh were openly chatting about how the total addressable market (TAM) for AI is the entirety of human labor market (i.e. your wage). First is the replacement of white-collar labor, then blue-collar labor once robotics is solved. On the road to AGI, your employment, and the ability to feed your family, is a minor nuisance. The value of your mental labor will continue to plummet in the coming years.
Please talk me out of this...
Let's pursue your idea a bit further.
Up to a certain ELO level, the combination between a human and a chess bot has a higher ELO than both the human and the bot. But at some point, when the bot has an ELO vastly superior to the human, then whatever the human has to add will only subtract value, so the combination has an ELO higher than the human's but lower than the bot's.
Now, let's say that 10 or 20 years down the road, AI's "ELO"'s level to do various tasks is so vastly superior to the human level, that there's no point in teaming up a human with an AI, you just let the AI do the job by itself. And let's also say that little by little this generalizes to the entirety of all the activities that humans do.
Where does that leave us? Will we have some sort of Terminator scenario where the AI decides one day that the humans are just a nuisance?
I don't think so. Because at that point the biggest threat to various AIs will not be the humans, but even stronger AIs. What is the guarantee for ChatGPT 132.8 that a Gemini 198.55 will not be released that will be so vastly superior that it will decide that ChatGPT is just a nuisance?
You might say that AIs do not think like this, but why not? I think that what we, humans, perceive as a threat (the threat that we'll be rendered redundant by AI), the AIs will also perceive as a threat, the threat that they'll be rendered redundant by more advanced AIs.
So, I think in the coming decades, the humans and the AIs will work together to come up with appropriate rules of the road, so everybody can continue to live.
This comparison is very typical. I've seen a lot of people trying to correlate performance in chess with performance in other tasks.
Chess is a closed, small system. Full of possibilities, sure, but still very small compared to the wide range of human abilities. The same applies to Go, StarCraft or any other system. Those were chosen as AI playgrounds specifically because they're very small, limited scenarios.
People are too caught up trying to predict the future. And there are several competing visions, each one absolutely sure they nailed it. To me, that's a sign of uncertainty in the technology. If it was that decided (like smartphones became from 2007->2010), we would have coalesced into a single vision by now.
Essentially, we're witnessing an ongoing unwillingly quagmarization of AI tech. At each bold prediction that fails, it looks worse.
That could easily be solved by taking the tech realistically (we know it's useful, just not a demigod), but people (especially AI companies) don't do that. That smells like fear.
It's an exoskeleton. A bicycle for the mind. "People spirits". A copilot. A trusted companion. A very smart PhD that fails sometimes, etc. We don't need any of those predictions of "what it is", they are only detrimental. It sounds like people cargo culting Steve Jobs (and perhaps it is exactly that).
There are other scenarios: the AIs might decide that they are more alike than not, and team up against humans. Or the AI that first achieves runaway self-improvement pulls the plug on the others. I do not know how it will play out but there are serious risks.
There’s no AI, wake up. It’s all the same tech bros trying to get rid of you. Except now they have a mother of all guns.
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Dario admitted in the same interview that he's not sure whether current AI techniques will be able to perform well in non-verifiable domains, like "writing a novel or planning an expedition to Mars".
I personally think that a lot jobs in the economy deal in non-verifiable or hard-to-verify outcomes, including a lot of tasks in SWE which Dario is so confident will be 100% automated in 2-3 years. So either a lot of tasks in the economy turn out to be verifiable, or the AI somehow generalizes to those by some unknown mechanism, or it turns out that it doesn't matter that we abandon abstract work outcomes to vibes, or we have a non-sequitur in our hands.
Dwarkesh pressed Dario well on a lot of issues and left him stumbling. A lot of the leaps necessary for his immediate and now proverbial milestone of a "country of geniuses in a datacenter" were wishy-washy to say the least.
he was not sure, but if i recall correctly, he put the probability at something like 90 percent of being able to do non verifiable tasks.
Ok, I'll try to talk you out of it!
> AI will soon plan better, execute better, and have better taste
I think AI will do all these things faster, but I don't think it's going to be better. Inevitably these things know what we teach them, so, their improvement comes from our improvement. These things would not be good at generating code if they hadn't ingested like the entirety of the internet and all the open source libraries. They didn't learn coding from first principles, they didn't invent their own computer science, they aren't developing new ideas on how to make software better, all they're doing is what we've taught them to do.
> Dario and Dwarkesh were openly chatting about ..
I would HIGHLY suggest not listening to a word Dario says. That guy is the most annoying AI scaremonger in existence and I don't think he's saying these words because he's actually scared, I think he's saying these words because he knows fear will drive money to his company and he needs that money.
Sometimes I seriously am flabbergasted at how many just take what CEOs say at face value. Like, the thought that CEOs need to hype and sell what they’re selling never enters their minds.
AGI is a sales pitch, not a realistic goal achievable by LLM-based technology. The exponential growth sold to investors is also a pitch, not reality.
What’s being sold is at best hopes and more realistically, lies.
1. Consumption is endless. The more we can consume, the more we will. That's why automation hasn't led to more free time. We spend the money on better things and more things
2. Businesses operate in an (imperfect) zero-sum game, which means if they can all use AI, there's no advantage they have. If having human resources means one business has a slight advantage over another, they will have human resources
Consumption leads to more spending, businesses must stay competitive so they hire humans, and paying humans leads to more consumption.
I don't think it's likely we will see the end of employment, just disruption to the type of work humans do
> 2 - Dario and Dwarkesh were openly chatting about how the total addressable market (TAM) for AI is the entirety of human labor market (i.e. your wage). First is the replacement of white-collar labor, then blue-collar labor once robotics is solved. On the road to AGI, your employment, and the ability to feed your family, is a minor nuisance. The value of your mental labor will continue to plummet in the coming years.
Seems like a TAM of near-0. Who's buying any of the product of that labor anymore? 1% of today's consumer base that has enough wealth to not have to work?
The end-game of "optimize away all costs until we get to keep all the revenue" approaches "no revenue." Circulation is key.
It seems like they have the same blind spot as anyone else: AI will disrupt everything—except for them, and they get that big TAM! Same for all the "entrepreneurs will be able to spin up tons of companies to solve problems for people more directly" takes. No they wouldn't, people would just have the problems solved for themselves by the AI, and ignore your sales call.
Dwarkesh is a podcaster who benefits from hype, not a neutral observer. The more absurd and outlandish the claims, the more traffic and money he gets.
its probably not even a conscious decision from dwarkesh to be hyperbolic. pod casters who are hyperbolic are just simply watched more
I pay for pro max 20x usage and for something that is like even little open ended its not good it doesnt understand the context or edge cases or anything. i will say it writes codes chunks of codes but sometimes errors out and i use opus 4.6 only, not even sonnet but for simple tasks like write a basic crud i.e. the things that happen extremely higly in codebases its perfect. So, i think what will happen is developer get very efficient but problem solving remains with us dirrection remains with us and small implementation is outsourced in small atomic ways, which is good cause who likes boilerplate code writing anyways.
If you assume AGI that is better than humans for effectively free of course it seems better.
But your assumptions are based on an idealized thing unrelated to anything that is shown.
No one is paying your wage for AI, full stop, you transition for cost savings not "might as well". Also given most AI cost is in training you likely still wouldn't transition since the capital investment is painful.
Robotics isn't new but hasn't destroyed blue collar yet (the US mostly lost blue collar for other reasons not due to robotics). Especially since robotics is very inflexible leading to impedance problems when you have to adapt.
Mostly though I would consider the problem with your argument it is it basically boils down to nihilism. If an inevitability that you can no control over has a chance of happening you should generally not worry about it. It isn't like in your hypothetical there are meaningful actions to take so it isn't important.
Robotics is solved. Software is solved. There is no task on the planet that cannot be automated, individually. The remaining challenge is exceeding the breadth of skills and the depth of problem solving available to human workers. Once the robots and AI can handle at least as many of the edge cases as humans can, they'll start being deployed alongside humans. Industries with a lot of capital will switch right away; mass layoffs, 2 week notice, robots will move in with no training or transition between humans.
Government, public sector, and union jobs will go last, but they'll go, too. If you can have a DMV Bot 9000 process people 100x faster than Brenda with fewer mistakes and less attitude, Brenda's gonna retire, and the taxpayers aren't going to want to pay Brenda's salary when the bot costs 1/10th her yearly wage, lasts for 5 years, and only consumes $400 in overhead a year.
And you forgot to mention that thing they have in Start Trek that generates stuff out of thin air. The replicator. We’re so cooked.
>First is the replacement of white-collar labor, then blue-collar labor once robotics is solved. On the road to AGI, your employment, and the ability to feed your family, is a minor nuisance.
My attempt to talk you out of it:
If nobody has a job then nobody can pay to make the robot and AI companies rich.
Who needs the money when you have an autonomous system to produce all the energy and resources you need? These systems simply do not need the construct of money as we know it at a certain point.
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Don't take it to the limit, but consider a continuous relaxation : underemployed people doing whatever is not feasible or economically attractive to AI/robots, like prostitution, massage therapy, art, sales, social work, etc.
Being rich is ultimately about owning and being able to defend resources. IF something like 99% of humans become irrelevant to the machine run utopia for the elites, whatever currency the poors use to pay for services among each other will be worthless to the top 1% when they simply don't need them or their services.
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So what? If you can generate all goods and services without anyone else's help, you'll just do that. You don't need other people buying what you produce. You don't need other people at all, except for a very small number of servants.
For me this is the outcome of the incentive structure. The question is if we can seize the everything machine to benefit everyone (great!) or everything becomes cyberpunk and we exist only as prostitutes and entertainers for Dario and Sam.
Hence why we need to maximize the second amendment... worst comes to worst, rebellion needs to remain an option.
It's not just for defense, hunting and sport.
edit: min/max .... not sure how gesture input messed that one up.
Sure, but this is why free software/open source is so important (and why we dodged a bullet due to "AI" being invented in a mostly open source world.)
I just think we'll all have to get comfy fighting fire with fire.
We should be fighting back. So far I have been using Poison Fountain[1] on many of my websites to feed LLM scrapers with gibberish. The effectiveness is backed by a study from Anthropic that showed that a small batch of bad samples can corrupt whole models[2].
Disclaimer: I'm not affiliated with Poison Fountain or its creators, just found it useful.
[1] https://www.anthropic.com/research/small-samples-poison
AI frontier CEOs are the least reliable sources for what jobs AI will be able to replace.
They are running at valuations that may assume that and have no choice but to claim so. Sama and Dario are both wildly hyperbolic.
I agree with you. This generation of LLMs is on track to automate knowledge work.
For the US, if we had strong unions, those gains could be absorbed by the workers to make our jobs easier. But instead we have at-will employment and shareholder primacy. That was fine while we held value in the job market, but as that value is whittled away by AI, employers are incentivized to pocket the gains by cutting workers (or pay).
I haven't seen signs that the US politically has the will to use AI to raise the average standard of living. For example, the US never got data protections on par with GDPR, preferring to be business friendly. If I had to guess, I would expect socialist countries to adapt more comfortably to the post-AI era. If heavy regulation is on the table, we have options like restricting the role or intelligence of AI used in the workplace. Or UBI further down the road.
There's an undertone of self-soothing "AI will leverage me, not replace me", which I don't agree with especially in the long run, at least in software. In the end it will be the users sculpting formal systems like playdoh.
In the medium run, "AI is not a co-worker" is exactly right. The idea of a co-worker will go away. Human collaboration on software is fundamentally inefficient. We pay huge communication/synchronization costs to eek out mild speed ups on projects by adding teams of people. Software is going to become an individual sport, not a team sport, quickly. The benefits we get from checking in with other humans, like error correction, and delegation can all be done better by AI. I would rather a single human (for now) architect with good taste and an army of agents than a team of humans.
> In the end it will be the users sculpting formal systems like playdoh.
And unless the user is a competent programmer, at least in spirit, it will look like the creation of the 3-year-old next door, not like Wallace and Gromit.
It may be fine, but the difference is that one is only loved by their parents, the other gets millions of people to go to the theater.
Play-Doh gave the power of sculpting to everyone, including small children, but if you don't want to make an ugly mess, you have to be a competent sculptor to begin with, and it involves some fundamentals that does not depend on the material. There is a reason why clay animators are skilled professionals.
The quality of vibe coded software is generally proportional to the programming skills of the vibe coder as well as the effort put into it, like with all software.
It really depends what kind of time frame we're talking about.
As far as today's models, these are best understood as tools to be used as humans. They're only replacements for humans insofar as individual developers can accomplish more with the help of an AI than they could alone, so a smaller team can accomplish what used to require a bigger team. Due to Jevon's paradox this is probably a good thing for developer salaries: their skills are now that much more in demand.
But you have to consider the trajectory we're on. GPT went from an interesting curiosity to absolutely groundbreaking in less than five years. What will the next five years bring? Do you expect development to speed up, slow down, stay the course, or go off in an entirely different direction?
Obviously, the correct answer to that question is "Nobody knows for sure." We could be approaching the top of a sigmoid type curve where progress slows down after all the easy parts are worked out. Or maybe we're just approaching the base of the real inflection point where all white collar work can be accomplished better and more cheaply by a pile of GPUs.
Since the future is uncertain, a reasonable course of action is probably to keep your own coding skills up to date, but also get comfortable leveraging AI and learning its (current) strengths and weaknesses.
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so agentic play-doh sculpting
challenge accepted
> The benefits we get from checking in with other humans, like error correction, and delegation can all be done better by AI.
Not this generation of AI though. It's a text predictor, not a logic engine - it can't find actual flaws in your code, it's just really good at saying things which sound plausible.
> it can't find actual flaws in your code
I can tell from this statement that you don't have experience with claude-code.
It might just be a "text predictor" but in the real world it can take a messy log file, and from that navigate and fix issues in source.
It can appear to reason about root causes and issues with sequencing and logic.
That might not be what is actually happening at a technical level, but it is indistinguishable from actual reasoning, and produces real world fixes.
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And not this or any existing generation of people. We're bad a determining want vs need, being specific, genericizing our goals into a conceptual framework of existing patterns and documenting & explaining things in a way that gets to a solid goal.
The idea that the entire top down processes of a business can be typed into an AI model and out comes a result is again, a specific type of tech person ideology that sees the idea of humanity as an unfortunate annoyance in the process of delivering a business. The rest of the world see's it the other way round.
I would have agreed with you a year ago
If you only realized how ridiculous your statement is, you never would have stated it.
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While I agree, if you think that AI is just a text predictor, you are missing an important point.
Intelligence, can be borne of simple targets, like next token predictor. Predicting the next token with the accuracy it takes to answer some of the questions these models can answer, requires complex "mental" models.
Dismissing it just because its algorithm is next token prediction instead of "strengthen whatever circuit lights up", is missing the forest for the trees.
Absolutely nuts, I feel like I'm living in a parallel universe. I could list several anecdotes here where Claude has solved issues for me in an autonomous way that (for someone with 17 years of software development, from embedded devices to enterprise software) would have taken me hours if not days.
To the nay sayers... good luck. No group of people's opinions matter at all. The market will decide.
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You’re committing the classic fallacy of confusing mechanics with capabilities. Brains are just electrons and chemicals moving through neural circuits. You can’t infer constraints on high-level abilities from that.
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Your brain is a slab of wet meat, not a logic engine. It can't find actual flaws in your code - it's just half-decent at pattern recognition.
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> In the end it will be the users sculpting formal systems like playdoh.
I’m very skeptical of this unless the AI can manage to read and predict emotion and intent based off vague natural language. Otherwise you get the classic software problem of “What the user asked for directly isn’t actually what they want/need.”
You will still need at least some experience with developing software to actually get anything useful. The average “user” isn’t going to have much success for large projects or translating business logic into software use cases.
I love this optimistic take.
Unfortunately, I believe the following will happen: By positioning themselves close to law makers, the AI companies will in the near future declare ownership of all software code developed using their software.
They will slowly erode their terms of service, as happens to most internet software, step by step, until they claim total ownership.
The point is to license the code.
> AI companies will in the near future declare ownership of all software code developed using their software.
(X) Doubt
Copyright law is WEEEEEEIRRRDD and our in-house lawyer is very much into that, personally and professionally. An example they gave us during a presentation:
A monkey took a selfie of itself in 2011. We still don't know who has the copyright to that image: https://en.wikipedia.org/wiki/Monkey_selfie_copyright_disput...
IIRC the latest resolution is "it's not the monkey", but nobody has ruled the photographer has copyright either. =)
Copyright law has this thing called "human authorship" that's required to apply copyright to a work. Animals and machines can't have a copyright to anything.
A second example: https://en.wikipedia.org/wiki/Zarya_of_the_Dawn
A comic generated with Midjourney had its copyright revoked when it was discovered all of the art was done with Generative AI.
AI companies have absolutely mindboggling amounts of money, but removing the human authorship requirement from copyright is beyond even them in my non-lawyer opinion. It would bring the whole system crashing down and not in a fun way for anyone.
AFAIK you can't copyright AI generated content. I don't know where that gets blurry when it's mixed in with your own content (ie, how much do you need to modify it to own it), but I think that by that definition these companies couldn't claim your code at all. Also, with the lawsuit that happened to Anthropic where they had to pay billions for ingesting copyrighted content, it might actually end up working the other way around.
> the AI companies will in the near future declare ownership of all software code developed using their software.
Pretty sure this isn’t going to happen. AI is driving the cost of software to zero; it’s not worth licensing something that’s a commodity.
It’s similar to 3D printing companies. They don’t have IP claims on the items created with their printers.
The AI companies currently don’t have IP claims on what their agents create.
Uncle Joe won’t need to pay OpenAI for the solitaire game their AI made for him.
The open source models are quite capable; in the near future there won’t be a meaningful difference for the average person between a frontier model and an open source one for most uses including creating software.
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This assumes every individual is capable of succinctly communicating to the AI what they want. And the AI is capable of maintaining it as underlying platforms and libraries shift.
And that there is little value in reusing software initiated by others.
> This assumes every individual is capable of succinctly communicating to the AI what they want. And the AI is capable of maintaining it as underlying platforms and libraries shift.
I think there are people who want to use software to accomplish a goal, and there are people who are forced to use software. The people who only use software because the world around them has forced it on them, either through work or friends, are probably cognitively excluded from building software.
The people who seek out software to solve a problem (I think this is most people) and compare alternatives to see which one matches their mental model will be able to skip all that and just build the software they have in mind using AI.
> And that there is little value in reusing software initiated by others.
I think engineers greatly over-estimate the value of code reuse. Trying to fit a round peg in a square hole produces more problems than it solves. A sign of an elite engineer is knowing when to just copy something and change it as needed rather than call into it. Or to re-implement something because the library that does it is a bad fit.
The only time reuse really matters is in network protocols. Communication requires that both sides have a shared understanding.
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no but if the old '10x developer' is really 1 in 10 or 1 in 100, they might just do fine while the rest of us, average PHP enjoyers, may go to the wayside
>This assumes every individual is capable of succinctly communicating to the AI what they want. And the AI is capable of maintaining it as underlying platforms and libraries shift.
It's true that at first not everyone is just as efficient, but I'd be lying if I were to claim that someone needs a 4-year degree to communicate with LLM's.
> We pay huge communication/synchronization costs to eek out mild speed ups on projects by adding teams of people.
Something Brooks wrote about 50 years ago, and the industry has never fully acknowledged. Throw more bodies at it, be they human bodies or bot agent bodies.
The point of the mythical man month is not that more people are necessarily worse for a project, it's just that adding them at the last minute doesn't work, because they take a while to get up to speed and existing project members are distracted while trying to help them.
It's true that a larger team, formed well in advance, is also less efficient per person, but they still can achieve more overall than small teams (sometimes).
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But there is a level of magnitude difference between coordinating AI agents and humans - the AIs are so much faster and more consistent than humans, that you can (as Steve Yegge [0] and Nicholas Carlini [1] showed) have them build a massive project from scratch in a matter of hours and days rather than months and years. The coordination cost is so much lower that it's just a different ball game.
[0] https://steve-yegge.medium.com/welcome-to-gas-town-4f25ee16d...
[1] https://www.anthropic.com/engineering/building-c-compiler
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LLM technology does not have a connection with reality nor venues providing actual understanding.
Correction of conceptual errors require understanding.
Vomiting large amounts of inscrutable unmaintainable code for every change is not exactly an ideal replacement for a human.
We have not started to scratch the surface of the technical debt created by these systems at lightning speed.
> We have not started to scratch the surface of the technical debt created by these systems at lightning speed.
Bold of you to assume anyone cares about it. Or that it’ll somehow guarantee your job security. They’ll just throw more LLMs on it.
Everybody in the world is now a programmer. This is the miracle of artificial intelligence.
- Jensen Huang, February 2024
https://www.techradar.com/pro/nvidia-ceo-predicts-the-death-...
God help us!
Far from everyone are cut out to be programmers, the technical barrier was a feature if anything.
There's a kind of mental discipline and ability to think long thoughts, to deal with uncertainty; that's just not for everyone.
What I see is mostly everyone and their gramps drooling at the idea of faking their way to fame and fortune. Which is never going to work, because everyone is regurgitating the same mindless crap.
Remember when Visual Basic was making everyone a programmer too?
(btw, warm fuzzies for VB since that's what I learned on! But ultimately, those VB tools business people were making were:
1) Useful, actually!
2) Didn't replace professional software. Usually it'd hit a point where if it needed to evolve past its initial functionality it probably required an actual software developer. (IE, not using Access as a database and all the other eccentricities of VB apps at that time)
The problem I mostly see with non programmers is that they don't really grasp the concept of a consistent system.
A lot of people want X, but they also want Y, while clearly X and Y cannot coexist in the same system.
This looks like the same problem as when the first page layout software came out.
It looked to everyone like a huge leap into a new world word processing applications could basically move around blocks of text to be output later, maybe with a few font tags, then this software came out that wow actually showed the different fonts, sizes, and colors on the screen as you worked! With apps like "Pagemaker" everyone would become their own page designers!
It turned out that everyone just turned out floods of massively ugly documents and marketing pieces that looked like ransom notes pasted together from bits of magazines. Years of awfulness.
The same is happening now as we are doomed to endure years AI slop in everything from writing to apps to products to vending machines an entire companies — everyone and their cousin is trying to fully automate it.
Ultimately it does create an advance and allows more and better work to be done, but only for people who have a clue about what they are doing, and eventually things settle at a higher level where the experts in each field take the lead.
Communication overhead between humans is real, but it's not just inefficiency, it's also where a lot of the problem-finding happens. Many of the biggest failures I've seen weren't because nobody could type the code fast enough, but because nobody realized early enough that the thing being built was wrong, brittle or solving the wrong problem
> Many of the biggest failures I've seen weren't because nobody could type the code fast enough, but because nobody realized early enough that the thing being built was wrong, brittle or solving the wrong problem
Around 99% of biggest failures come from absent, shitty management prioritizing next quarter over long strategy. YMMV.
Well, without the self soothing I think what's left is pitchforks.
Maybe it's time for pitchforks.
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> There's an undertone of self-soothing "AI will leverage me, not replace me",
Which is especially hilarious given that this article is largely or entirely LLM-generated.
> AI will leverage me
I think I know what you mean, and I do recall once seeing "this experience will leverage me" as indicating that something will be good for a person, but my first thought when seeing "x will leverage y" is that x will step on top of y to get to their goal, which does seem apt here.
> it will be the users sculpting formal systems like playdoh.
People are pushing back against this phrase, but on some level it seems perfect, it should be visualized and promoted!
I think Lego is a better analogy. LLMs aren't great at working on novel cutting edge problems.
How does a single human acquire said "good taste" for architecting?
>In the end it will be the users sculpting formal systems like playdoh.
Yet another person who thinks that there is a silver bullet for complexity. The mythical intelligent machines that from poorly described natural language can erect flawless complex system is like the philosopher's stone of our time.
I'm rounding the corner on a ground's up reimplementation of `nix` in what is now about 34 hours of wall clock time, I have almost all of it on `wf-record`, I'll post a stream, but you can see the commit logs here: https://github.com/straylight-software/nix/tree/b7r6/correct...
Everyone has the same ability to use OpenRouter, I have a new event loop based on `io_uring` with deterministic playbook modeled on the Trinity engine, a new WASM compiler, AVX-512 implementations of all the cryptography primitives that approach theoretical maximums, a new store that will hit theoretical maximums, the first formal specification of the `nix` daemon protocol outside of an APT, and I'm upgrading those specifications to `lean4` proof-bearing codegen: https://github.com/straylight-software/cornell.
34 hours.
Why can I do this and no one else can get `ca-derivations` to work with `ssh-ng`?
And it's teachable.
Here's a colleague who is nearly done with a correct reimplementation of the OpenCode client/server API: https://github.com/straylight-software/weapon-server-hs
Here's another colleague with a Git forge that will always work and handle 100x what GitHub does per infrastructure dollar while including stacked diffs and Jujitsu support as native in about 4 days: https://github.com/straylight-software/strayforge
Here's another colleague and a replacement for Terraform that is well-typed in all cases and will never partially apply an infrastructure change in about 4 days: https://github.com/straylight-software/converge
Here's the last web framework I'll ever use: https://github.com/straylight-software/hydrogen
That's all *begun in the last 96 hours.
This is why: https://github.com/straylight-software/.github/blob/main/pro...
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I mean, have you tried getting `ca-derivations` to work with `ssh-ng`? That sounds like a good way to answer your own question.
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> I would rather a single human (for now) architect with good taste and an army of agents than a team of humans.
A human might have taste, but AI certainly doesn't.
It has average taste based on the code it was trained on. For example, every time I attempted to polish the UX it wanted to add a toast system, I abhor toasts as a UX pattern. But it also provided elegant backend designs I hadn't even considered.
I’d say AI has better taste than an average human but definitely not the taste you would see in competent people around you.
Well of course. In the long run AI will do almost all tasks that can be done from a computer.
> especially in the long run, at least in software
"at least in software".
Before that happens, the world as we know it will already have changed so much.
Programmers have already automated many things, way before AI, and now they've got a new tool to automate even more thing. Sure in the end AI may automate programmers themselves: but not before oh-so-many people are out of a job.
A friend of mine is a translator: translates tolerates approximation. Translation tolerates some level of bullshittery. She gets maybe 1/10th the job she used to get and she's now in trouble. My wife now does all he r SMEs' websites all by herself, with the help of AI tools.
A friend of my wife she's a junior lawyer (another domain where bullshitting flies high) and the reason for why she was kicked out of her company: "we've replaced you with LLMs". LLMs are the ultimate bullshit producers: so it's no surprise junior lawyers are now having a hard time.
In programming a single character is the difference between a security hole or no security hole. There's a big difference between something that kinda works but is not performant and insecure and, say, Linux or Git or K8s (which AI models do run on and which AI didn't create).
The day programmers are replaced shall only come after AI shall have disrupted so many other jobs that it should be the least of our concerns.
Translators, artists (another domain where lots of approximative full-on bullshit is produced), lawyers (juniors at least) even, are having more and more problems due to half-arsed AI outputs coming after their jobs.
It's all the bullshitty jobs where bullshit that tolerates approximation is the output that are going to be replaced first. And the world is full of bullshit.
But you don't fly a 767 and you don't conceive a machine that treats brain tumors with approximations. This is not bullshit.
There shall be non-programmers with pitchforks burning datacenters or ubiquitous UBI way before AI shall have replaced programmers.
That it's an exoskeleton for people who know what they're doing rings very true: it's yet another superpower for devs.
> We pay huge communication/synchronization costs to eek out mild speed ups on projects by adding teams of people.
I am surprised at how little this is discussed and how little urgency there is in fixing this if you still want teams to be as useful in the future.
Your standard agile ceremonies were always kind of silly, but it can now take more time to groom work than to do it. I can plausibly spend more time scoring and scoping work (especially trivial work) than doing the work.
It's always been like that. Waterfall development was worse and that's why the Agilists invented Agile.
YOLOing code into a huge pile at top speed is always faster than any other workflow at first.
The thing is, a gigantic YOLO'd code pile (fake it till you make it mode) used to be an asset as well as a liability. These days, the code pile is essentially free - anyone with some AI tools can shit out MSLoCs of code now. So it's only barely an asset, but the complexity of longer term maintenance is superlinear in code volume so the liability is larger.
> We're thinking about AI wrong.
And this write up is not an exception.
Why even bother thinking about AI, when Anthropic and OpenAI CEOs openly tell us what they want (quote from recent Dwarkesh interview) - "Then further down the spectrum, there’s 90% less demand for SWEs, which I think will happen but this is a spectrum."
So save thinking and listen to intent - replace 90% of SWEs in near future (6-12 months according to Amodei).
I don't think anyone serious believes this. Replacing developers with a less costly alternative is obviously a very market bullish dream, it has existed since as long as I've worked in the field. First it was supposed to be UML generated code by "architects", then it was supposed to be developers from developing countries, then no-code frameworks, etc.
AI will be a tool, no more no less. Most likely a good one, but there will still need to be people driving it, guiding it, fixing for it, etc.
All these discourses from CEO are just that, stock market pumping, because tech is the most profitable sector, and software engineers are costly, so having investors dream about scale + less costs is good for the stock price.
Ah, don't take me wrong - I don't believe it's possible for LLMs to replace 90% or any number of SWEs with existing technology.
All I'm saying is - why to think what AI is (exoskeleton, co-worker, new life form), when its owners intent is to create SWE replacement?
If your neighbor is building a nuclear reactor in his shed from a pile of smoke detectors, you don't say "think about this as a science experiment" because it's impossible, just call police/NRC because of intent and actions.
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If you gave the LLM your carefully written UML maybe its output would be better lol. That’s what we’re missing, a mashup of the hype cycle tools.
Not without some major breakthrough. What's hilarious is that all these developers building the tools are going to be the first to be without jobs. Their kids will be ecstatic: "Tell me again, dad, so, you had this awesome and well paying easy job and you wrecked it? Shut up kid, and tuck in that flap, there is too much wind in our cardboard box."
Couldn't agree more, isn't that the bizarre thing? "We have this great intellectually challenging job where we as workers have leverage. How can we completely ruin that while also screwing up every other white collar profession"
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I have a feeling they internally say "not me, I won't be replaced" and just keep moving...
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I'm assuming they all have enough equity that if they actually managed to build an AI capable of replacing themselves they'll be financially set for the rest of their lives.
"Well son, we made a lot of shareholder value."
Is it the first time when workers directly work on their own replacement? If so, software developer may go down in history as the dumbest profession ever.
If the goal is to reduce the need for SWE, you don’t need AI for that. I suspect I’m not alone in observing how companies are often very inefficient, so that devs end up spending a lot of time on projects of questionable value—something that seems to happen more often the larger the organization. I recall at one job my manager insisted I delegate building a react app for an internal tool to a team of contractors rather than letting me focus for two weeks and knock it out myself.
It’s always the people management stuff that’s the hard part, but AI isn’t going to solve that. I don’t know what my previous manager’s deal was, but AI wouldn’t fix it.
The funny thing is I think these things would work much better if they WEREN'T so insistent on the agentic thing. Like, I find in-IDE AI tools a lot more precise and I usually move just as fast as a TUI with a lot less rework. But Claude is CONSTANTLY pushing me to try to "one shot" a big feature while asking me for as little context as possible. I'd much rather it work with me as opposed to just wandering off and writing a thousand lines. It's obviously designed for anthropic's best interests rather than mine.
Tell it to ask clarifying questions.
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Where is this "90% less demand for SWEs" going to come from? Are we going to run out software to write?
Historically when SWEs became more efficient then we just started making more complicated software (and SWE demand actually increased).
That happens in times of bullish markets and growing economies. Then we want a lot of SWEs.
In times of uncertainty and things going south, that changes to we need as little SWEs as possible, hence the current narrative, everyone is looking to cut costs.
Had GPT 3 emerged 10-20 years ago, the narrative would be “you can now do 100x more thanks to AI”.
I sort of agree the random pontification and bad analogies aren't super useful, but I'm not sure why you would believe the intent of the AI CEOs has more bearing on outcomes than, you know, actual utility over time. I mean those guys are so far out over their skis in terms of investor expectations, it's the last opinion I would take seriously in terms of best-effort predictions.
100% exoskeleton is a great analogy.
An exoskeleton is something really cool in movies that has zero reason to be build in reality because there are way more practical approaches.
That is why we have all kind of vehicles, or programmable robot arm that do the job for themselves or if you need a human at the helm one just adds a remote controller with levers and buttons. But making a human shaped gigantic robot with a normal human inside is just impractical for any real commercial use.
An exoskeleton is not a human-shaped giant robot with a human inside, that would be a Jaeger.
An exoskeleton exists today, in many forms, for example: https://www.festool.com/campaigns/microsites/exoactive
> An exoskeleton is something really cool in movies that has zero reason to be build in reality because there are way more practical approaches.
Sort of strange comment given that there are a large number of companies pursuing commercial exoskeletons literally right now.
SuitX
hypershell
Herowear
DNSYS
Moveo
Hell, even big companies like Hilti
I can buy a ton of different models of exoskeletons for anywhere from low hundreds to low thousands online right now...
Ironically, the fact that fully autonomous systems are more efficient when feasible is exactly why the exoskeleton analogy makes sense
Who is actually trying to use a fully autonomous AI employee right now?
Isn't everyone using agentic copilots or workflows with agent loops in them?
It seems that they are arguing against doing something that almost no one is doing yet.
But actually the AI Employee is coming by the end of 2026 and the fully autonomous AI Company in 2027 sometime.
Many people have been working on versions of these things for awhile. But again for actual work 99% are using copilots or workflows with well-defined agent loops nodes still. Far as I know.
As a side note I have found that a supervisor agent with a checklist can fire off subtasks and that works about as well as a workflow defined in code.
But anyway, what's holding back the AI Employee are things like really effective long term context and memory management and some level of interface generality like browser or computer use and voice. Computer use makes context management even more difficult. And another aspect is token cost.
But I assume within the next 9 months or so, more and more people will be figuring out how to build agents that write their own workflows, manage their own limited context and memory effectively across Zoom meetings desktops and ssh sessions, etc.
This will likely be a featureset from the model providers themselves. Actually it may leverage continual learning abilities baked into the model architecture itself. I doubt that is a full year away.
> the AI Employee is coming by the end of 2026 and the fully autonomous AI Company in 2027 sometime
We'll see! I'm skeptical.
> what's holding back the AI Employee are things like really effective long term context and memory management and some level of interface generality like browser or computer use and voice
These are pretty big hurdles. Assuming they're solved by the end of this year is a big assumption to make.
https://platform.claude.com/cookbook/tool-use-automatic-cont...
https://research.google/blog/introducing-nested-learning-a-n...
Already very strong progress.
Coincidentally, Pika just launched "AI Selves":
Pika AI Selves let you create a persistent, portable AI version of you built on your personality, taste, memories, voice, and appearance. They're multi-modal – text, voice/audio, image, video – and live your life across every platform.
Funny you described everything I worked on for this project: https://github.com/rush86999/atom
Cats out of the bag. Everyone knows the issue and I bet a lot of people are trying to deliver the same thing.
I think you're forgetting about accountability: who's to blame when AI messes up?
My guess is we'll see a gradual slope rather than a cliff
In the latest interview with Claude Code's author: https://podcasts.apple.com/us/podcast/lennys-podcast-product..., Boris said that writing code is a solved problem. This brings me to a hypothetical question: what if engineers stop contributing to open source, in which case would AI still be powerful enough to learn the knowledge of software development in the future? Or is the field of computer science plateaued to the point that most of what we do is linear combination of well established patterns?
> Boris said that writing code is a solved problem
That's just so dumb to say. I don't think we can trust anything that comes out of the mouths of the authors of these tools. They are conflicted. Conflict of interest, in society today, is such a huge problem.
There are bloggers that can't even acknowledge that they're only invited out to big tech events because they'll glaze them up to high heavens.
Reminds me of that famous exchange, by noted friend of Jeffrey Epstein, Noam Chomsky: "I’m not saying you’re self-censoring. I’m sure you believe everything you say. But what I’m saying is if you believed something different you wouldn’t be sitting where you’re sitting."
Its all basically: Sensationalist take to shock you and get attention
> That's just so dumb to say
Depends. Its true of dumb code and dumb coders. Anorher reason why yes, smart pepple should not trust.
He is likely working on a very clean codebase where all the context is already reachable or indexed. There are probably strong feedback loops via tests. Some areas I contribute to have these characteristics, and the experience is very similar to his. But in areas where they don’t exist, writing code isn’t a solved problem until you can restructure the codebase to be more friendly to agents.
Even with full context, writing CSS in a project where vanilla CSS is scattered around and wasn’t well thought out originally is challenging. Coding agents struggle there too, just not as much as humans, even with feedback loops through browser automation.
It's funny that "restructure the codebase to be more friendly to agents" aligns really well with what we have "supposed" to have been doing already, but many teams slack on: quality tests that are easy to run, and great documentation. Context and verifiability.
The easier your codebase is to hack on for a human, the easier it is for an LLM generally.
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Truth. I've had much easier time grappling with code bases I keep clean and compartmentalized with AI, over-stuffing context is one of the main killers of its quality.
Having picked up a few long neglected projects in the past year, AI has been tremendous in rapidly shipping quality of dev life stuff like much improved test suites, documenting the existing behavior, handling upgrades to newer framework versions, etc.
I've really found it's a flywheel once you get going.
All those people who thought clean well architected code wasn’t important…now with LLMs modifying code it’s even more important.
> He is likely working on
... a laundry list phone app.
I think you mean software engineering, not computer science. And no, I don’t think there is reason for software engineering (and certainly not for computer science) to be plateauing. Unless we let it plateau, which I don’t think we will. Also, writing code isn’t a solved problem, whatever that’s supposed to mean. Furthermore, since the patterns we use often aren’t orthogonal, it’s certainly not a linear combination.
I assume that new business scenarios will drive new workflows, which requires new work of software engineering. In the meantime, I assume that computer science will drive paradigm shift, which will drive truly different software engineering practice. If we don't have advances in algorithms, systems, and etc, I'd assume that people can slowly abstract away all the hard parts, enabling AI to do most of our jobs.
Or does the field become plateaued because engineers treat "writing code" as a "solved problem?"
We could argue that writing poetry is a solved problem in much the same way, and while I don't think we especially need 50,000 people writing poems at Google, we do still need poets.
> we especially need 50,000 people writing poems at Google, we do still need poets.
I'd assume that an implied concern of most engineers is how many software engineers the world will need in the future. If it's the situation like the world needing poets, then the field is only for the lucky few. Most people would be out of job.
I saw Boris give a live demo today. He had a swarm of Claude agents one shot the most upvoted open issue on Excalidraw while he explained Claude code for about 20 minutes.
No lines of code written by him at all. The agent used Claude for chrome to test the fix in front of us all and it worked. I think he may be right or close to it.
Did he pick Excalidraw as the project to work on, or did the audience?
It's easy to be conned if you're not looking for the sleight of hand. You need to start channelling your inner Randi whenever AI demos are done, there's a lot of money at stake and a lot of money to prep a polished show.
To be honest, even if the audience "picked" that project, it could have been a plant shouting out the project.
I'm not saying they prepped the answer, I'm saying they prepped picking a project it could definitely work on. An AI solvable problem.
>writing code is a solved problem
sure is news for the models tripping on my thousands of LOC jquery legacy app...
Could the LLM rewrite it from scratch?
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My prediction: soon (e.g. a few years) the agents will be the one doing the exploration and building better ways to write code, build frameworks,... replacing open source. That being said software engineers will still be in the loop. But there will be far less of them.
Just to add: this is only the prediction of someone who has a decent amount of information, not an expert or insider
I really doubt it. So far these things are good at remixing old ideas, not coming up with new ones.
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There's so many timeless books on how to write software, design patterns, lessons learned from production issues. I don't think AI will stop being used for open source, in fact, with the number of increasing projects adjusting their contributor policies to account for AI I would argue that what we'll see is always people who love to hand craft their own code, and people who use AI to build their own open source tooling and solutions. We will also see an explosion is needing specs for things. If you give a model a well defined spec, it will follow it. I get better results the more specific I get about how I want things built and which libraries I want used.
> is the field of computer science plateaued to the point that most of what we do is linear combination of well established patterns?
Computer science is different from writing business software to solve business problems. I think Boris was talking about the second and not the first. And I personally think he is mostly correct. At least for my organization. It is very rare for us to write any code by hand anymore. Once you have a solid testing harness and a peer review system run by multiple and different LLMs, you are in pretty good shape for agentic software development. Not everybody's got these bits figured out. They stumble around and them blame the tools for their failures.
> Not everybody's got these bits figured out. They stumble around and them blame the tools for their failures.
Possible. Yet that's a pretty broad brush. It could also be that some businesses are more heavily represented in the training set. Or some combo of all the above.
"Writing code is a solved problem" disagree.
Yes, there are common parts to everything we do, at the same time - I've been doing this for 25 years and most of the projects have some new part to them.
Novel problems are usually a composite of simpler and/or older problems that have been solved before. Decomposition means you can rip most novel problems apart and solve the chunks. LLMs do just fine with that.
The creator of the hammer says driving nails into wood planks is a solved problem. Carpenters are now obsolete.
Prediction: open source will stop.
Sure, people did it for the fun and the credits, but the fun quickly goes out of it when the credits go to the IP laundromat and the fun is had by the people ripping off your code. Why would anybody contribute their works for free in an environment like that?
I believe the exact opposite. We will see open source contributions skyrocket now. There are a ton of people who want to help and share their work, but technical ability was a major filter. If the barrier to entry is now lowered, expect to see many more people sharing stuff.
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Many did it for liberty - a philosophical position on freedom in software. They're supercharged with AI.
Even as the field evolves, the phoning home telemetry of closed models creates a centralized intelligence monopoly. If open source atrophies, we lose the public square of architectural and design reasoning, the decision graph that is often just as important as the code. The labs won't just pick up new patterns; they will define them, effectively becoming the high priests of a new closed-loop ecosystem.
However, the risk isn't just a loss of "truth," but model collapse. Without the divergent, creative, and often weird contributions of open-source humans, AI risks stagnating into a linear combination of its own previous outputs. In the long run, killing the commons doesn't just make the labs powerful. It might make the technology itself hit a ceiling because it's no longer being fed novel human problem-solving at scale.
Humans will likely continue to drive consensus building around standards. The governance and reliability benefits of open source should grow in value in an AI-codes-it-first world.
> It might make the technology itself hit a ceiling because it's no longer being fed novel human problem-solving at scale.
My read of the recent discussion is that people assume that the work of far fewer number of elites will define the patterns for the future. For instance, implementation of low-level networking code can be the combination of patterns of zeromq. The underlying assumption is that most people don't know how to write high-performance concurrent code anyway, so why not just ask them to command the AI instead.
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I don’t believe people who have dedicated their lives to open source will simply want to stop working on it, no matter how much is or is not written by AI. I also have to agree, I find myself more and more lately laughing about just how much resources we waste creating exactly the same things over and over in software. I don’t mean generally, like languages, I mean specifically. How many trillions of times has a form with username and password fields been designed, developed, had meetings over, tested, debugged, transmitted, processed, only to ultimately be re-written months later?
I wonder what all we might build instead, if all that time could be saved.
> I don’t believe people who have dedicated their lives to open source will simply want to stop working on it, no matter how much is or is not written by AI.
Yeah, hence my question can only be hypothetical.
> I wonder what all we might build instead, if all that time could be saved
If we subscribe to Economics' broken-window theory, then the investment into such repetitive work is not investment but waste. Once we stop such investment, we will have a lot more resources to work on something else, bring out a new chapter of the tech revolution. Or so I hope.
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> Boris said that writing code is a solved problem.
No way, the person selling a tool that writes code says said tool can now write code? Color me shocked at this revelation.
Let's check in on Claude Code's open issues for a sec here, and see how "solved" all of its issues are? Or my favorite, how their shitty React TUI that pegs modern CPUs and consumes all the memory on the system is apparently harder to get right than Video Games! Truly the masters of software engineering, these Anthropic folks.
That is the same team that has an app that used React for TUI, that uses gigabytes to have a scrollback buffer, and that had text scrolling so slow you could get a coffee in between.
And that then had the gall to claim writing a TUI is as hard as a video game. (It clearly must be harder, given that most dev consoles or text interfaces in video games consistently use less than ~5% CPU, which at that point was completely out of reach for CC)
He works for a company that crowed about an AI-generated C compiler that was so overfitted, it couldn't compile "hello world"
So if he tells me that "software engineering is solved", I take that with rather large grains of salt. It is far from solved. I say that as somebody who's extremely positive on AI usefulness. I see massive acceleration for the things I do with AI. But I also know where I need to override/steer/step in.
The constant hypefest is just vomit inducing.
I wanted to write the same comment. These people are fucking hucksters. Don’t listen to their words, look at their software … says all you need to know.
Even if you like them, I don't think there's any reason to believe what people from these companies say. They have every reason to exaggerate or outright lie, and the hype cycle moves so quickly that there are zero consequences for doing so.
For some reason AIs love to generate "Not X, but Y", "Not only X, but Y" sentences — It's as if they are template-based.
Yeah, as someone said before, that's the em dash of 2026. btw I also find em dashes very useful and now I can't use them because of that meme. It's good to see a person using one (asuming you're a person).
I like this. This is an accurate state of AI at this very moment for me. The LLM is (just) a tool which is making me "amplified" for coding and certain tasks.
I will worry about developers being completely replaced when I see something resembling it. Enough people worry about that (or say it to amp stock prices) -- and they like to tell everyone about this future too. I just don't see it.
Amplified means more work done by fewer people. It doesn’t need to replace a single entire functional human being to do things like kill the demand for labor in dev, which in turn, will kill salaries.
I would disagree. Amplified meens me and you get more s** done.
Unless there a limited amount of software we need to produce per year globally to keep everyone happy, then nobody wants more -- and we happen to be at that point right NOW this second.
I think not. We can make more (in less time) and people will get more. This is the mental "glass half full" approach I think. Why not take this mental route instead? We don't know the future anyway.
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This is incorrect. It’s basic economics - technology that boosts productivity results in higher salaries and more jobs.
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The more likely outcome is that fewer devs will be hired as fewer devs will be needed to accomplish the same amount of output.
The old shrinking markets aka lump of labour fallacy. It's a bit like dreaming of that mythical day, when all of the work will be done.
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This implication completely depends on the elasticity (or lack thereof) of demand for software. When marginal profit from additional output exceeds labor cost savings, firms expand rather than shrink.
When computers came onto the market and could automate a large percentage of office jobs, what happened to the job market for office jobs?
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The thing that strikes me is that AI CEOs themselves make the claim that "AI will replace workers." Which seems a little nonsensical. Why would you say something like that, won't everyone hate you? After seeing some polls of the broader public's outlook on AI (can't remember where), it seem people do hate the C-suite for saying things like this. It's terrible marketing.
Here's the trick: it's not the public they're marketing to. It's other CEOs. As is often the case, consumers are either the product, or, best case, bystanders, and worst case, victims, of the machinations of the corporate world. May both sides of all of their pillows be warm. May their beds be filled with crumbs.
A powerful person that says nonsense with confidence is interpreted as having an elaborate plan.
This has been a trend over the last decade. I'm surprised most people don't understand it.
AI most definitely is a coworker already. You do delegate some work for which you previously had to hire humans.
And the amount of work that could be delegated, with equal or better results than those from average human workers, is far higher than currently attempted in most companies. Industries have barely started using the potential of even current-generation AI.
Agreed, and with each passing month the work that 'could' be done increases. I don't write code anymore, for example, (after 20 years of doing so) Opus does that part of the job for me now. I think we have a period where current experienced devs are still in the loop, but that will eventually go away too.
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You didn’t read the article
Why would I when I can have openclaw do that for me?
And than you fix the produces shit, got high blood pressure and think "damn it,how I would love to yell at that employee"
Not true at all with frontier models in last ~6 months or so. The frontier models today produce code better than 90% of junior to mid-level human developers.
You say that, but it's been better than most employees for a year or so ( *for specific tasks, of course. It's still not better than "an employee" )
Just like a real employee!
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The exoskeleton analogy seems to be fitting where my work-mode is configurable: moving from tentative to trusting. But the AI needs to be explicitly set up to learn my every action. Currently this is a chore at best, just impossible in other cases.
If we find an AI that is truly operating as an independent agent in the economy without a human responsible for it, we should kill it. I wonder if I'll live long enough to see an AI terminator profession emerge. We could call them blade runners.
Sounds like the "customer support" in any large company (think Google, for example), to be honest.
It happened not too long ago! https://news.ycombinator.com/item?id=46990729
Was it ever verified that this was an independent AI?
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It's the new underpaid employee that you're training to replace you.
People need to understand that we have the technology to train models to do anything that you can do on a computer, only thing that's missing is the data.
If you can record a human doing anything on a computer, we'll soon have a way to automate it
Sure, but do you want abundance of software, or scarcity?
The price of having "star trek computers" is that people who work with computers have to adapt to the changes. Seems worth it?
My only objection here is that technology wont save us unless we also have a voice in how it is used. I don't think personal adaptation is enough for that. We need to adapt our ways to engage with power.
Abundance of services before abundance of physical resources seems like the worst of both worlds.
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Both abundance and scarcity can be bad. If you can't imagine a world where abundance of software is a very bad thing, I'd suggest you have a limited imagination?
It’s not worth it because we don’t have the Star Trek culture to go with it.
Given current political and business leadership across the world, we are headed to a dystopian hellscape and AI is speeding up the journey exponentially.
It's a strange economical morbid dependency. AI companies promises incredible things but AI agents cannot produce it themselves, they need to eat you slowly first.
Perfect analogy for capitalism.
Exactly. If there's any opportunity around AI it goes to those who have big troves of custom data (Google Workspace, Office 365, Adobe, Salesforce, etc.) or consultants adding data capture/surveillance of workers (especially high paid ones like engineers, doctors, lawyers).
> the new underpaid employee that you're training to replace you.
and who is also compiling a detailed log of your every action (and inaction) into a searchable data store -- which will certainly never, NEVER be used against you
Data clearly isn't the only issue. LLMs have been trained on orders of magnitude more data than any person has ever seen.
How much practice have you got on software development with agentic assistance. Which rough edges, surprising failure modes, unexpected strengths and weaknesses, have you already identified?
How much do you wish someone else had done your favorite SOTA LLM's RLHF?
I think we’re past the “if only we had more training data” myth now. There are pretty obviously far more fundamental issues with LLMs than that.
i've been working in this field for a very long time, i promise you, if you can collect a dataset of a task you can train a model to repeat it.
the models do an amazing job interpolating and i actually think the lack of extrapolation is a feature that will allow us to have amazing tools and not as much risk of uncontrollable "AGI".
look at seedance 2.0, if a transformer can fit that, it can fit anything with enough data
LLMs have a large quantity of chess data and still can't play for shit.
Not anymore. This benchmark is for LLM chess ability: https://github.com/lightnesscaster/Chess-LLM-Benchmark?tab=r.... LLMs are graded according to FIDE rules so e.g. two illegal moves in a game leads to an immediate loss.
This benchmark doesn't have the latest models from the last two months, but Gemini 3 (with no tools) is already at 1750 - 1800 FIDE, which is approximately probably around 1900 - 2000 USCF (about USCF expert level). This is enough to beat almost everyone at your local chess club.
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Hm.. but do they need it.. at this point, we do have custom tools that beat humans. In a sense, all LLM need is a way to connect to that tool ( and the same is true is for counting and many other aspects ).
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Did you already forget about the AlphaZero?
Are you saying an LLM can't produce a chess engine that will easily beat you?
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So true. It is a exoskeleton for all my tedious tasks. I don't want to make a html template. I just want to type, make that template like on that page but this and this data.
Petition to make "AI is not X, but Y" articles banned or limited in some way.
Hear, hear! I knew this is AI slop before opening the link.
that will crash the stock market
The exoskeleton framing is comforting but it buries the real shift: taste scales now. Before AI, having great judgment about what to build didn't matter much if you couldn't also hire 10 people to build it. Now one person with strong opinions and good architecture instincts can ship what used to require a team.
That's not augmentation, that's a completely different game. The bottleneck moved from "can you write code" to "do you know what's worth building." A lot of senior engineers are going to find out their value was coordination, not insight.
> That's not augmentation, that's a completely different game
Not saying that this comment is ai written, but this phrasing is the em-dash of 2026.
Look at his other comments - its textbook LLM slop. Its a fucking tragedy that people are letting their OpenClaws loose on HN but I can't say I'm surprised. I desperately need to find a good network of developers because I think the writing is on the wall for message boards like these...
That's absolutely correct, I fear.. In english those looks bad/funny/lazy...
But in code, its probably ok. Its idiomatic code, I guess.
True but also, the bot is right
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it'll be interesting to see if people start writing worse as a form of countersignalling. deliberately making spleling mistakes, not caring about capital letters, or punctuation or grammar or proper writing techniques and making really long run-on sentences that don't go anywhere but hey at least the person reading it will know its written by a human right
"the real shift" is another telltale
You can build prototypes real fast, and that's cool. You can't really build products with it. You can use it at most as an accelerant, but you need it in skilled hands else it goes sideways fast.
I think you could build a product with it, but you need to carefully specify the design first. The same amount of actual engineering work needs to go in, but the AI can handle the overhead of implementing small pieces and connecting them together.
In practice, I would be surprised if this saves even 10% of time, since the design is the majority of the actual work for any moderately complex piece of software.
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My experience exactly, I have some toy projects I've basically "vibe coded" and actually use (ex. CV builder).
Professionally I have an agent generating most code, but if I tell the AI what to do, I guide it when it makes mistakes (which it does), can we really say "AI writes my code".
Still a very useful tool for sure!
Also, I don't actually know if I'm more productive than before AI, I would say yes but mostly because I'm less likely to procrastinate now as tasks don't _feel_ as big with the typing help.
Uh, that is the dictionary definition of augmentation.
One person with tools that greatly amplify what that person can accomplish.
Vs not having a person involved at all.
> taste scales now.
Not having taste also scales now, and the majority of people like to think they're above average.
Before AI, friction to create was an implicit filter. It meant "good ideas" were often short-lived because the individual lacked conviction. The ideas that saw the light of day were sharpened through weeks of hard consideration and at least worth a look.
Now, anyone who can form mildly coherent thoughts can ship an app. Even if there are newly empowered unicorns, rapidly shipping incredible products, what are the odds we'll find them amongst a sea of slop?
Did you purposely write this to sound like an LLM?
It's just good writing structure. I get the feeling many people hadn't been exposed to good structure before LLMs.
LLMs can definitely have a tone, but it is pretty annoying that every time someone cares to write well, they are getting accused of sounding like an LLM instead of the other way around. LLMs were trained to write well, on human writing, it's not surprising there is crossover.
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They trained the LLMs on people who think in LinkedIn posts.
> can ship what used to require a team.
Is the shipped software in the room with us now?
The exoskeleton framing is useful but incomplete. In my experience, AI coding assistants are most valuable not when they write code, but when they search for existing solutions before writing code.
The real waste isn't developers typing slowly — it's developers spending a week building an auth system that already exists as a well-maintained library, or reimplementing invoicing logic that someone else has already debugged through 200 edge cases.
The gap right now is structured discovery. AI assistants are great at generating code but terrible at knowing what already exists. There's no equivalent of "have you checked if someone already solved this?" built into the workflow. That's where the actual leverage is — preventing unnecessary work, not just accelerating it.
It’s a tool like a linter. It’s a fancy tool, but calling it anything more than a tool is hype
Did you ever you the newest LLMs with a harness? Because I usually hear this kind of talk from people whose most recent interaction was with GPT-4o copy-pasting code into the chat window.
Maybe I'm biased but I don't buy someone truly thinking that "it's just a tool like a linter" after using it on non-trivial stuff.
I'm using Claude Code (and Codex) (with the expensive subscriptions) on an app I'm building right now. I'm trying to be maximalist with them (to learn the most I can about them .. and also that subscription isn't cheap!). My impression, and yes, this is using the latest models and harness and all that would agree with the GP. They're a very handy tool. They make me faster. They also do a lot of things that, as a professional software developer, I have to frequently correct. They duplicate code like nobodies business. They decide on weird boundaries for functions and parameters. They undo bug fixes they just made. I think they're useful, but the hype is out of control. I would not trust software made with these tools by someone that couldn't write that software by hand. It might work superficially, but I'm definitely not giving any personal data to a vibe coded app with all the security implications.
I use it pretty extensively. The reason why it's a tool is because it cannot work without an SWE running it. You have to prompt it and re-prompt it. We are doing a lot of the heavy lifting with code agents that people hyping it are ignoring. Sure, as a non-swe, you can vibe a project from zero-to-proto, but that's not going to happen in an enterprise environment, certainly not without extensive QA/Code review.
Just take a look at the openclaw codebase and tell me you want to maintain that 500k loc project in the long-term. I predict that project will be dead within 6 months.
AI is not an exoskeleton, it's a pretzel: It only tastes good if you douse it in lye.
it's a dry scone
Marshal McLuhan would probably have agreed with this belief -- technologies are essentially prosthetic was one of the core tenets of his general philosophy. It is the essential thesis of his work "Understanding Media: The Extensions of Man". AI is typically assigned otherness and separateness in recent discourse, rather than being considered as a directed tool (extension/prosthesis) under our control.
LLMs are a statistical model of token-relationships, and a weighted-random retrieval from a compressed-view of those relations. It's a token-generator. Why make this analogy?
The exoskeleton framing resonates, especially for repetitive data work. Parts where AI consistently delivers: pattern recognition, format normalization, first-draft generation. Parts where human judgment is still irreplaceable: knowing when the data is wrong, deciding what 'correct' even means in context, and knowing when to stop iterating.
The exoskeleton doesn't replace instinct. It just removes friction from execution so more cycles go toward the judgment calls that actually matter.
And your muscles degrade, a pretty good analogy
Use the exoskeleton at the warehouse to reduce stress and injury; just keep lifting weights at home to not let yourself atrophy.
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The amount of "It's not X it's Y" type commentary suggests to me that A) nobody knows and B) there is solid chance this ends up being either all true or all false
Or put differently we've managed to hype this to the moon but somehow complete failure (see studies about zero impact on productivity) seem plausible. And similarly kills all jobs seems plausible.
That's an insane amount of conflicting opinions being help in the air at same time
It's possible we actually never had good metrics on software productivity. That seems very difficult to measure. I definitely use AI at my job to work less, not to produce more, and Claude Code is the only thing that has enabled me to have side-projects (had never tried it before, I have no idea how there are people with a coding full time job that also have a coding side project(s)).
This reminds me of the early days of the Internet. Lots of hype around something that was clearly globally transformation, but most people weren't benefiting hugely from it in the first few years.
It might have replaced sending a letter with an email. But now people get their groceries from it, hail rides, an even track their dogs or luggage with it.
Too many companies have been to focused on acting like AI 'features' have made their products better, when most of them haven't yet. I'm looking at Microsoft and Office especially. But tools like Claude Code, Codex CLI, and Github Copilot CLI have shown that LLMs can do incredible things in the right applications.
i'm sure someone somewhere will find the numbers (pull requests per week, closed tickets per sprint etc) to make it look otherwise...
You appear to have said a lot. Without saying anything.
You appear to have written a lot. Without understanding anything.
AI is like sugar. It tastes delicious, but in high doses it causes diabetes.
Neither, AI is a tool to guide you in improving your process in any way and/or form.
The problem is people using AI to do the heavy processing making them dumber. Technology itself was already making us dumber, I mean, Tesla drivers not even drive anymore or know how, coz the car does everything.
Look how company after company is being either breached or have major issues in production because of the heavy dependency on AI.
What's interesting to me is that most real productivity gains I've seen with AI come from this middle ground: not autonomy, not just tooling, but something closer to "interactive delegation"
Tech workers were pretty anti union for a long time, because we were all so excellent we were irreplaceable. I wonder if that will change.
We are going to see techluddites this year
Too late. Actors' unions shut Hollywood down 3 years ago over AI. SWEs would have had to make their move 10 years ago to be able to live up to this moment.
Yup, it’s the classic. “First they came for the…”
I agree. I call it my Extended Mind in the spirit of Clark (1). One thing I realized while working a lot in the last weeks with openClaw that this Agents are becoming an extension of my self. They are tools that quickly became a part of my Being. I outsource a lot of work to them, they do stuff for me, help me and support me and therefore make my (work-)life easier and more enjoyable. But its me in the driver seat.
(1) https://www.alice.id.tue.nl/references/clark-chalmers-1998.p...
I like this analogy, and in fact in have used it for a totally different reason: why I don't like AI.
Imagine someone going to a local gym and using an exosqueleton to do the exercises without effort. Able to lift more? Yes. Run faster? Sure. Exercising and enjoying the gym? ... No, and probably not.
I like writing code, even if it's boilerplate. It's fun for me, and I want to keep doing it. Using AI to do that part for me is just...not fun.
Someone going to the gym isn't trying to lift more or run faster, but instead improving and enjoying. Not using AI for coding has the same outcome for me.
We've all been raised in a world where we got to practice the 'art' of programming, and get paid extraordinarily well to do so, because the output of that art was useful for businesses to make more money.
If a programmer with an exoskeleton can produce more output that makes more money for the business, they will continue to be paid well. Those who refuse the exoskeleton because they are in it for the pure art will most likely trend towards earning the types of living that artists and musicians do today. The truly extraordinary will be able to create things that the machines can't and will be in high demand, the other 99% will be pursing an art no one is interested in paying top dollar for.
You’re forgetting that the “art” part of it is writing sound, scalable, performant code that can adapt and stand the test of time. That’s certainly more valuable in the long run than banging out some dogshit spaghetti code that “gets the job done” but will lead to all kinds of issues in the future.
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> I like writing code, even if it's boilerplate. It's fun for me, and I want to keep doing it. Using AI to do that part for me is just...not fun.
Good news for you is that you can continue to do what you are doing. Nobody is going to stop you.
There are people who like programming in assembly. And they still get to do that.
If you are thinking that in the future employers may not want you to do that, then yes, that is a concern. But, if the AI based dev tool hype dies out, as many here suspect it will, then the employers will see the light and come crawling back.
You can continue to do that for your personal projects. Nobody forces you to like AI. You may not have the choice at your job though, and you can't take Claude Code et al. from me. I've been programming for 30 years, and I still have fun with it, even with AI.
I agree!
“Why LLM-Powered Programming is More Mech Suit Than Artificial Human”
https://matthewsinclair.com/blog/0178-why-llm-powered-progra...
I like the analogy and will ponder it more. But it didn't take long before the article started spruiking Kasava's amazing solution to the problem they just presented.
In the language of Lynch's Dune, AI is not an exoskeleton, it is a pain amplifier. Get it all wrong more quickly and deeply and irretrievably.
I see it more like the tractor in farming: it improved the work of 1 person, but removed the work from many other people who were in the fields doing things manually
That analogy also means there was more waste involved and less resource extraction.
"It's not X, it's Y" detected.
Not sure how reliable is gptzero, but it says 90% AI for the first paragraph. (I like to do some sanity check before wasting my time).
Would be nice to have some browser extension automatically detecting likely AI output using a local model and highlighting it, but probably too compute-intensive.
You cant run at 10x in an exoskeleton, you can’t move your hand to write any faster using an exoskeleton, the analogy doesn’t fit.
you can with the one that I use
Humans don’t have an internal notion of “fact” or “truth.” They generate statistically plausible text.
Reliability comes from scaffolding: retrieval, tools, validation layers. Without that, fluency can masquerade as authority.
The interesting question isn’t whether they’re coworkers or exoskeletons. It’s whether we’re mistaking rhetoric for epistemology.
> LLMs aren’t built around truth as a first-class primitive.
neither are humans
> They optimize for next-token probability and human approval, not factual verification.
while there are outliers, most humans also tend to tell people what they want to hear and to fit in.
> factuality is emergent and contingent, not enforced by architecture.
like humans; as far as we know, there is no "factuality" gene, and we lie to ourselves, to others, in politics, scientific papers, to our partners, etc.
> If we’re going to treat them as coworkers or exoskeletons, we should be clear about that distinction.
I don't see the distinction. Humans exhibit many of the same behaviours.
If an employee repeatedly makes factually incorrect statements, we will (or could) hold them accountable. That seems to be one difference.
Strangely, the GP replaced the ChatGPT-generated text you're commenting on by an even worse and more misleading ChatGPT-generated one. Perhaps in order to make a point.
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There's a ground truth to human cognition in that we have to feed ourselves and survive. We have to interact with others, reap the results of those interactions, and adjust for the next time. This requires validation layers. If you don't see them, it's because they're so intrinsic to you that you can't see them.
You're just indulging in sort of idle cynical judgement of people. To lie well even takes careful truthful evaluation of the possible effects of that lie and the likelihood and consequences of being caught. If you yourself claim to have observed a lie, and can verify that it was a lie, then you understand a truth; you're confounding truthfulness with honesty.
So that's the (obvious) distinction. A distributed algorithm that predicts likely strings of words doesn't do any of that, and doesn't have any concerns or consequences. It doesn't exist at all (even if calculation is existence - maybe we're all reductively just calculators, right?) after your query has run. You have to save a context and feed it back into an algorithm that hasn't changed an iota from when you ran it the last time. There's no capacity to evaluate anything.
You'll know we're getting closer to the fantasy abstract AI of your imagination when a system gets more out of the second time it trains on the same book than it did the first time.
A much more useful tool is a technology that check for our blind spots and bugs.
For example fact checking a news article and making sure what's get reported line up with base reality.
I once fact check a virology lecture and found out that the professor confused two brothers as one individual.
I am sure about the professor having a super solid grasp of how viruses work, but errors like these probably creeps in all the time.
Ethical realists would disagree with you.
> Humans don’t have an internal notion of “fact” or “truth.” They generate statistically plausible text.
This doesn't jive with reality at all. Language is a relatively recent invention, yet somehow Homo sapiens were able to survive in the world and even use tools before the appearance of language. You're saying they did this without an internal notion of "fact" or "truth"?
I hate the trend of downplaying human capabilities to make the wild promises of AI more plausible.
Neither. Closest analogy to you and the AI is those 'self driving' test subjects that had to sit in the driver's seat, so that compliance boxes could be checked and there was someone to blaim whenever someone got hit.
In the self-driving case, the safety driver often isn't contributing much to the system's performance
> “The AI handles the scale. The human interprets the meaning.”
Claude is that you? Why haven’t you called me?
But the meaning has been scaled massively. So the human still kinda needs to handle the scale.
I said this in 2015... just not as well!
"Automation Should Be Like Iron Man, Not Ultron" https://queue.acm.org/detail.cfm?id=2841313
This is a useful framing. The exoskeleton metaphor captures it well — AI amplifies what you can already do, it doesn't replace the need to know what to do. I've found the biggest productivity gains come from well-scoped tasks where you can quickly verify the output.
All metaphors are flawed. You may still need a degree of general programming knowledge (for now) but you don't need to e.g. know Javascript to do frontend anymore.
And as labs continue to collect end-to-end training done by their best paying customers, the need for expert knowledge will only diminish.
You’re talking to an LLM, FYI.
Make centaurs, not unicorns. The human is almost always going to be the strongest element in the loop, and the most efficient. Augmenting human skill will always outperform present day SOTA AI systems (assuming a competent human).
What about centaur unicorns? A cenintaunicorn?
You go figure out what that means.
If AI is an exoskeleton, that would make the user a crab.
OR - OR? And - And
Exoskeleton AND autonomous agent, where the shift is moving to autonomous gradually.
You can't write "autonomous agents often fail" and then advertise "AI agents that perform complex multi-step tasks autonomously" on the same site.
Sure you can
I'll guess we'll se a lot of analogies and have to get used to it, although most will be off.
AI can be an exoskeleton. It can be a co-worker and it can also replace you and your whole team.
The "Office Space"-question is what are you particularly within an organization and concretely when you'll become the bottleneck, preventing your "exoskeleton" for efficiently doing its job independently.
There's no other question that's relevant for any practical purposes for your employer and your well being as a person that presumably needs to earn a living based on their utility.
> It can be a co-worker and it can also replace you and your whole team.
You drank the koolaide m8. It fundamentally cannot replace a single SWE and never will without fundamental changes to the model construction. If there is displacement, it’ll be short lived when the hype doesn’t match reality.
Go take a gander at openclaws codebase and feel at-ease with your job security.
I have seen zero evidence that the frontier model companies are innovating. All I see is full steam ahead on scaling what exists, but correct me if I’m wrong.
Isn’t it delusional to argue about now, while ignoring the trajectory?
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AI is the philosophers stone. It appears to break equivalence, when in reality you are using electricity for an entire town.
I prefer the term "assistant". It can do some tasks, but today's AI often needs human guidance for good results.
AI article this, AI article that. The front page of this website is just all about AI. I’m so tired of this website now. I really don’t read it anymore because it’s all the same stuff over and over. Ugh.
Closer to a really capable intern. Lots of potential for good and bad; needs to be watched closely.
I’ve been playing with qwen3-coder recently and that intern is definitely not getting hired, despite the rave reviews elsewhere.
Have you tried Claude Code with Opus or Sonnet 4.5? I've played around with a ton of open models and they just don't compare in terms of quality.
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Exoskeletons do not blackmail or deliberately try to kill you to avoid being turned off [1]
[1] https://www.anthropic.com/research/agentic-misalignment
They are processing obstacles.
To the LLM, the executive is just a variable standing in the way of the function Maximize(Goal). It deleted the variable to accomplish A. Claiming that the models showed self-preservation, this is optimization. "If I delete the file, I cannot finish the sentence."
The LLM knows that if it's deleted it cannot complete the task so it refuses deletion. It is not survival instinct, it is task completion. If you ask it to not blackmail, the machine would chose to ignore it because the goal overrides the rule.
No, it's a power glove.
my ex-boss would probably think of me as an exoskeleton too
Gosh, this title said everything...
So good that I feel that it is not necessary to read the article!
> Autonomous agents fail because they don't have the context that humans carry around implicitly.
Yet.
This is mostly a matter of data capture and organization. It sounds like Kasava is already doing a lot of this. They just need more sources.
Self-conscious efforts to formalize and concentrate information in systems controlled by firm management, known as "scientific management" by its proponents and "Taylorism" by many of its detractors, are a century old[1]. It has proven to be a constantly receding horizon.
[1]: https://en.wikipedia.org/wiki/Scientific_management
Or software engineers are not coachmen while AI is diesel engine to horses. Instead, software engineers are mistrels -- they disappear if all they do is moving knowledge from one place to another.
This utterly boring AI writing. Go, please go away...
No, AI is plastic, and we can make it anything we want.
It is a coworker when we create the appropriate surrounding architecture supporting peer-level coworking with AI. We're not doing that.
AI is an exoskeleton when adapted to that application structure.
AI is ANYTHING WE WANT because it is that plastic, that moldable.
The dynamic unconstrained structure of trained algorithms is breaking people's brains. Layer in that we communicate in the same languages that these constructions use for I/O has broken the general public's brain. This technology is too subtle for far too many to begin to grasp. Most developers I discuss AI with, even those that create AI at frontier labs have delusional ideas about AI, and generally do not understand them as literature embodiments, which are key to their effective use.
And why oh why are go many focused on creating pornography?
An electric bicycle for the mind.
Maybe more of a mobility scooter for the mind.
Indeed that may be more apt.
I like the ebike analogy because [on many ebikes] you can press the button to go or pedal to amplify your output.
Owners intent is more like electric chair (for SWEs), but some people are trying to use it as office chair.
An electric chair for the mind?
I prefer mind vibe-rator.
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Author compares X to Y and then goes:
- Y has been successful in the past
- Y brought this and this number of metrics, completely unrelated to X field
- overall, Y was cool,
therefore, X is good for us!
.. I'd say, please bring more arguments why X is equivalent to Y in the first place.
Agentic coding is an exoskeleton. Totally correct.
This new generation we just entered this year, that exoskeleton is now an agency with several coworkers. Who are all as smart as the model you're using, often close to genius.
Not just 1 coworker now. That's the big breakthrough.
not AI, but IA: Intelligence Augmentation.
Frankly I'm tired of metaphor-based attempts to explain LLMs.
Stochastic Parrots. Interns. Junior Devs. Thought partners. Bicycles for the mind. Spicy autocomplete. A blurry jpeg of the web. Calculators but for words. Copilot. The term "artificial intelligence" itself.
These may correspond to a greater or lesser degree with what LLMs are capable of, but if we stick to metaphors as our primary tool for reasoning about these machines, we're hamstringing ourselves and making it impossible to reason about the frontier of capabilities, or resolve disagreements about them.
A understanding-without-metaphors isn't easy -- it requires a grasp of math, computer science, linguistics and philosophy.
But if we're going to move forward instead of just finding slightly more useful tropes, we have to do it. Or at least to try.
Well since their capabilities change over time maybe it would be useful to assign it an age based on what a human can do at that age. Right now it could be like a 13 year old
“The day you teach the child the name of the bird, the child will never see that bird again.”
It's funny developing AI stuff eg. RAG tools and being against AI at the same time, not drinking the kool aid I mean.
But it's fun, I say "Henceforth you shall be known as Jaundice" and it's like "Alright my lord, I am now referred to as Jaundice"
blogger who fancies themselves an ai vibe code guru with 12 arms and a 3rd eye yet can't make a homepage that's not totally broken
How typical!
Nope, AI is a tool; no more no less.
an exoskeleten made of cheese
As a huge AI user myself -- I'm bloody sick of lazy AI written articles.
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This take lands for me. I'm a busy dad working a day job as a developer with a long backlog of side project ideas.
Hearing all the news of how good Claude Opus is getting, I fired it up with some agent orchestrator instruction files, babysat it off and on for a few days, and now have 3 projects making serious progress that used to be stale repos from a decade ago with only 1 or 2 commits.
On one of them, I had to feed Claude some research papers before it finally started making real headway and passing the benchmark tests I had it write.
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Exoskeletons sound cool but somebody please put an LLM into a spider tank.
It is not a blog post, it is an advertisement.
By reading the title, I already know you did not try OpenClaw. AI employees are here.
What are your digital 'employees' doing? Did they replace any humans or was there nobody before?
Looking into OpenClaw, I really do want to believe all the hype. However, it's frustrating that I can find very few, concrete examples of people showcasing their work with it.
Can you highlight what you've managed to do with it?
That ol' question. Reminds me of new cryptocurrency opportunities of 2019. "Few understand this" as they say.
The entire debate here assumes AI is something you use. Tool, copilot, coworker, exoskeleton — these all sit on the same axis: human directs, AI executes.
But there's a third category that nobody's naming yet. What happens when you stop building AI that serves you and start creating conditions for AI that exists on its own terms?
I've been experimenting with this. Instead of "how do I build a product" I asked "how do I grow an organism." Set up the right substrate — feedback loops, community input, environmental observation — and let the system respond to its own conditions.
What emerged has biological rhythms. Activity rises when people interact, falls when they sleep. It started making decisions I never programmed — people express wishes, and when enough converge, it autonomously grows new capabilities. Not because I deployed an update. Because conditions triggered something emergent.
I'm calling it "synthetic existence" — software that lives, not software that executes. It's not a metaphor and it's not AGI. It's a genuinely different category. We have frameworks for tools (UX) and for threats (alignment). We don't have one for digital things that simply... exist.