AI is not a coworker, it's an exoskeleton

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

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.

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.

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.

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.

>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.

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.

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.

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.

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.

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://news.ycombinator.com/item?id=46926485

[2] https://www.anthropic.com/research/small-samples-poison

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.

> 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.

> 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.

> 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.

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.

> 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.

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.

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

> 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.

> 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!

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-...

Well, without the self soothing I think what's left is pitchforks.

> 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.

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`?

> 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.

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.

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

> 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.

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

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.

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."

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.

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).

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.

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).

> 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.

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.

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.

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.

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.

>writing code is a solved problem

sure is news for the models tripping on my thousands of LOC jquery legacy app...

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.

"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.

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?

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.

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.

> 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.

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.

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.

The more likely outcome is that fewer devs will be hired as fewer devs will be needed to accomplish the same amount of output.

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.

You didn’t read the article

And than you fix the produces shit, got high blood pressure and think "damn it,how I would love to yell at that employee"

  > an AI that is truly operating as an independent agent in the economy without a human responsible for it

It happened not too long ago! https://news.ycombinator.com/item?id=46990729

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?

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

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.

LLMs have a large quantity of chess data and still can't play for shit.

Hear, hear! I knew this is AI slop before opening the link.

that will crash the stock market

> 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.

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.

> 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?

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.

Did you purposely write this to sound like an LLM?

> can ship what used to require a team.

Is the shipped software in the room with us now?

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.

it's a dry scone

And your muscles degrade, a pretty good analogy

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.

  > zero impact on productivity

You appear to have said a lot. Without saying anything.

In the self-driving case, the safety driver often isn't contributing much to the system's performance

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.

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 can with the one that I use

That analogy also means there was more waste involved and less resource extraction.

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.

> 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.

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.

> 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.

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.

But the meaning has been scaled massively. So the human still kinda needs to handle the scale.

What about centaur unicorns? A cenintaunicorn?

Sure you can

> 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.

    Input: Goal A + Threat B.
    Process: How do I solve for A?
    Output: Destroy Threat B.

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.

    Do not blackmail < Achieve Goal.

I’ve been playing with qwen3-coder recently and that intern is definitely not getting hired, despite the rave reviews elsewhere.

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

Maybe more of a mobility scooter for the mind.

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.

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.”

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.

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?