> If you want to argue seriously, you have to start with ground truth. What is happening now. What the trendlines look like. What follows if those trendlines continue.

Wait, so we can infer the future from "trendlines", but not from past events? Either past events are part of a macro trend, and are valuable data points, or the micro data points you choose to focus on are unreliable as well. Talk about selection bias...

I would argue that data points that are barely a few years old, and obscured by an unprecedented hype cycle and gold rush, are not reliable predictors of anything. The safe approach would be to wait for the market to settle, before placing any bets on the future.

> Time from idea to implementation is collapsing. Junior and mid level work is disappearing first. Teams are shipping with fewer people. These are not hypotheticals.

What is hypothetical is what will happen to all this software and the companies that produced it a few years down the line. How reliable is it? How maintainable is it? How many security issues does it have? What has the company lost because those issues were exploited? Will the same people who produced it using these new tools be able to troubleshoot and fix it? Will the tools get better to allow them to do that?

> The reason this argument keeps reappearing has little to do with tools and everything to do with identity.

Really? Everything? There is no chance that some people are simply pointing out the flaws of this technology, and that the marketing around it is making it out to be far more valuable than it actually is, so that a bunch of tech grifters can add more zeroes to their net worth?

I don't get how anyone can speak about trends and what's currently happening with any degree of confidence. Let alone dismiss the skeptics by making wild claims about their character. Do better.

If past events can be dismissed as “noise,” then so can selectively chosen counterexamples. Either historical outcomes are legitimate inputs into a broader signal, or no isolated datapoint deserves special treatment. You cannot appeal to trendlines while arbitrarily discarding the very history that defines them without committing selection bias.

When large numbers of analogous past events point in contradictory directions, individual anecdotes lose predictive power. Trendlines are not an oracle, but once the noise overwhelms the signal, they are the best approximation we have.

>What is hypothetical is what will happen to all this software and the companies that produced it a few years down the line. How reliable is it? How maintainable is it? How many security issues does it have? What has the company lost because those issues were exploited? Will the same people who produced it using these new tools be able to troubleshoot and fix it? Will the tools get better to allow them to do that?

These are legitimate questions, and they are all speculative. My expectation is that code quality will decline while simultaneously becoming less relevant. As LLMs ingest and reason over ever larger bodies of software, human oriented notions of cleanliness and maintainability matter less. LLMs are far less constrained by disorder than humans are.

>Really? Everything? There is no chance that some people are simply pointing out the flaws of this technology, and that the marketing around it is making it out to be far more valuable than it actually is, so that a bunch of tech grifters can add more zeroes to their net worth?

The flaws are obvious. So obvious that repeatedly pointing them out is like warning that airplanes can crash while ignoring that aviation safety has improved to the point where you are far more likely to die in a car than in a metal tube moving at 500 mph.

Everyone knows LLMs hallucinate. That is not contested. What matters is the direction of travel. The trendline is clear. Just as early aviation was dangerous but steadily improved, this technology is getting better month by month.

That is the real disagreement. Critics focus on present day limitations. Proponents focus on the trajectory. One side freezes the system in time; the other extrapolates forward.

>I don’t get how anyone can speak about trends and what’s currently happening with any degree of confidence. Let alone dismiss the skeptics by making wild claims about their character. Do better.

Because many skeptics are ignoring what is directly observable. You can watch AI generate ultra complex, domain specific systems that have never existed before, in real time, and still hear someone dismiss it entirely because it failed a prompt last Tuesday.

Repeating the limitations is not analysis. Everyone who is not a skeptic already understands them and has factored them in. What skeptics keep doing is reciting known flaws while refusing to reason about what is no longer a limitation.

At that point, the disagreement stops being about evidence and starts looking like bias.

There is one painfully obvious, undeniable historical trend: making programmer work easier increases the number of programmers. I would argue a modern developer is 1000x more effective than one working in the times of punch cards - yet we have roughly 1000x more software developers than back then.

I'm not an AI skeptic by any means, and use it everyday at my job where I am gainfully employed to develop production software used by paying customers. The overwhelming consensus among those similar to me (I've put down all of these qualifiers very intentionally) is that the currently existing modalities of AI tools are a massive productivity boost mostly for the "typing" part of software (yes, I use the latest SOTA tools, Claude Opus 4.5 thinking, blah, blah, so do most of my colleagues). But the "typing" part hasn't been the hard part for a while already.

You could argue that there is a "step change" coming in the capabilities of AI models, which will entirely replace developers (so software can be "willed into existence", as elegantly put by OP), but we are no closer to that point now than we were in December 2022. All the success of AI tools in actual, real-world software has been in tools specifically design to assist existing, working, competent developers (e.g. Cursor, Claude Code), and the tools which have positioned themselves to replace them have failed (Devin).

I responded to another person in this thread and it’s the same response I would throw at you. You can read that as well.

Your “historical trend” is just applying an analogy and thinking that an analogy can take the place of reasoning. There are about a thousand examples of careers where automation technology increased the need of human operators and thousands of examples where automation eliminated human operators. Take pilots for example. Automation didn’t lower the need for pilots. Take intellisense and autocomplete… That didn’t lower the demand for programmers.

But then take a look at Waymo. You have to be next level stupid to think that ok, cruise control in cars raised automation but didn’t lower the demand for drivers… Therefore all car related businesses including Waymo will always need physical drivers.

As anyone is aware… this idea of using analogy as reasoning fails here. Waymo needs zero physical drivers thanks to automation. There is zero demand here and your methodology of reasoning fails.

Analogies are a form of manipulation. They only help allow you to elucidate and understand things via some thread of connection. You understand A therefore understanding A can help you understand B. But you can’t use analogies as the basis for forecasting or reasoning because although A can be similar to B, A is not in actuality B.

For AI coders it’s the same thing. You just need to use your common sense rather than rely on some inaccurate crutch of analogies and hoping everything will play out in the same way.

If AI becomes as good and as intelligent as a human swe than your job is going out the fucking window and replaced by a single Prompter. That’s common sense.

Look at the actual trendline of the actual topic: AI taking over our jobs and not automation in other sectors of engineering or other types of automation in software. What happened with AI in the last decade? We went from zero to movies, music and coding. What does your common sense tell you the next decade will bring?

If the improvement of AI from the last decade keeps going or keeps accelerating, the conclusion is obvious.

Sometimes the delusion a lot of swes have is jarring. Like literally if AGI existed thousands of jobs will be displaced. That’s common sense, but you still see tons of people clinging to some irrelevant analogy as if that exact analogy will play out against common sense.

My argument isn't an analogy - it's an observation based on the trajectory of SWE employment specifically. It's you who's trying to reason about what's going to happen with software based on what happened to three-field crop rotation or whatever, not me.

I argued that a developer today is 1000x more effective than in the days of punch cards, yet we have 1000x more developers today. Not only that, this correlation tracked fairly linearly throughout the last many decades.

I would also argue that the productivity improvement between FORTRAN and C, or between C and Python was much, much more impactful than going from JavaScript to JavaScript with ChatGPT.

Software jobs will be redefined, they will require different skill sets, they may even be called something else - but they will still be there.

Bro I offered you analogies to show you how it's IRRELEVANT. The point was to show you how it's an ineffective form of reasoning via demonstrating it's ineffectiveness FOR YOUR conclusion because using this reasoning can allow you to conclude the OPPOSITE. Assuming this type of reasoning is effective means BOTH what I say is true and what you say is true which leads to a logical contradiction.

There is no irony, only misunderstanding from you.

>I argued that a developer today is 1000x more effective than in the days of punch cards, yet we have 1000x more developers today. Not only that, this correlation tracked fairly linearly throughout the last many decades.

See here, you're using an analogy and claiming it's effective. To which I would typically offer you another analogy that shows the opposite effect, but I feel it would only confuse you further.

>Software jobs will be redefined, they will require different skill sets, they may even be called something else - but they will still be there.

Again, you believe this because of analogies. I recommend you take a stab at my way of reasoning. Try to arrive at your own conclusion without using analogies.

I'm yet to be convinced of this. I keep hearing it, but every time I look at the results they're basically garbage.

I think LLMs are useful tools, but I haven't seen anything convincing that they will be able to replace even junior developers any time soon.

What does common sense tell you the next decade will bring? Does the trendline predict flat lining that LLMs or AI in general won’t improve? Or will the trendline continue like most trendlines typically trend on doing? What is the most logical conclusion?

https://xkcd.com/605/

I have no doubt LLMs will continue to improve, but no idea at what rate and what the limit will be.

> When large numbers of analogous past events point in contradictory directions, individual anecdotes lose predictive power. Trendlines are not an oracle, but once the noise overwhelms the signal, they are the best approximation we have.

I'm confused. So you're agreeing with me, up until the very last part of the last sentence...? If the "noise overwhelms the signal", why are "trendlines the best approximation we have"? We have reliable data of past outcomes in similar scenarios, yet the most recent noisy data is the most valuable? Huh?

(Honestly, your comments read suspiciously like they were LLM-generated, as others have mentioned. It's like you're jumping on specific keywords and producing the most probable tokens without any thought about what you're saying. I'll give you the benefit of the doubt for one more reply, though.)

To be fair, I think this new technology is fundamentally different from all previous attempts at abstracting software development. And I agree with you that past failures are not necessarily indicative that this one will fail as well. But it would be foolish to conclude anything about the value of this technology from the current state of the industry, when it should be obvious to anyone that we're in a bull market fueled by hype and speculation.

What you're doing is similar to speculative takes during the early days of the internet and WWW. How it would transform politics, end authoritarianism and disinformation, and bring the world together. When the dust settled after the dot-com crash, actual value of the technology became evident, and it turns out that none of the promises of social media became true. Quite the opposite, in fact. That early optimism vanished along the way.

The same thing happened with skepticism about the internet being a fad, that e-commerce would never work, and so on. Both groups were wrong.

> What skeptics keep doing is reciting known flaws while refusing to reason about what is no longer a limitation. At that point, the disagreement stops being about evidence and starts looking like bias.

Skepticism and belief are not binary states, but a spectrum. At extreme ends there are people who dismiss the technology altogether, and there are people who claim that the technology will cure diseases, end poverty, and bring world prosperity[1].

I think neither of these viewpoints are worth paying attention to. As usual, the truth is somewhere in the middle. I'm leaning towards the skeptic side simply because the believers are far louder, more obnoxious, and have more to gain from pushing their agenda. The only sane position at this point is to evaluate the technology based on personal use, discuss your experience with other rational individuals, and wait for the hype to die down.

[1]: https://ai-2027.com/

Let me help you untangle the confusion. Historical data on other phenomenons is not a trendline for AI taking over your job. It's a typical logical mistake people make. It's reasoning via analogy. Because this trend happened for A, and A fits B like an analogy therefore what happened to A must happen to B.

Why is that stupid logic? Because there are thousands of things that fit B as an analogy. And out of those thousands of things that fit, some failed and some succeeded. What you're doing and not realizin is you are SELECTIVELY picking the analogy you like to use as evidence.

When I speak of a trendline. It's deadly simple. Literally look at AI as it is now, as it is in the past and use that to project into the future. Look at exact data of the very thing you are measuring rather then trying to graft some analogous thing onto the current thing and make a claim from that.

>What you're doing is similar to speculative takes during the early days of the internet and WWW. How it would transform politics, end authoritarianism and disinformation, and bring the world together. When the dust settled after the dot-com crash, actual value of the technology became evident, and it turns out that none of the promises of social media became true. Quite the opposite, in fact. That early optimism vanished along the way.

Again same thing. The early days of the internet is not what's happening to AI currently. You need to look at what happened to AI and software from the beginning to now. Observe the trendline of the topic being examined.

>I think neither of these viewpoints are worth paying attention to. As usual, the truth is somewhere in the middle. I'm leaning towards the skeptic side simply because the believers are far louder, more obnoxious, and have more to gain from pushing their agenda. The only sane position at this point is to evaluate the technology based on personal use, discuss your experience with other rational individuals, and wait for the hype to die down.

Well if you look at the pace and progress of AI, the quantitative evidence points against your middle ground opinion here. It's fashionable to take the middle ground because moderates and grey areas seem more level headed and reasonable than extremism. But this isn't really applicable to reality is it? Extreme events that overload systems happen in nature all the time, taking the middle ground without evidence pointing to the middle ground is pure stupidity.

So all you need to look at is this, in the past decade look at the progress we've made until now. A decade ago AI via ML was non-existent. Now AI generates movies, music and code, and unlike AI in music and movies, code is being in actuality used by engineers.

That's ZERO to coding in a decade. What do you think the next decade will bring. Coding to what? That is reality and the most logical analysis. Sure it's ok to be a skeptic, but to ignore the trendline is ignorance.

My dude, I just want to point out that there is no evidence of any of this, and a lot of evidence of the opposite.

> If you want to engage honestly, you stop citing the past and start following the numbers. You accept where the trendlines lead, even

You first, lol.

> This is how self delusion works

Yeah, about that...

“You first, lol” isn’t a rebuttal either. It’s an evasion. The claim was not “the labor market has already flipped.” The claim was that AI-assisted coding has changed individual leverage, and that extrapolating that change leads somewhere uncomfortable. Demanding proof that the future has already happened is a category error, not a clever retort.

And yes, the self-delusion paragraph clearly hit, because instead of addressing it, you waved vaguely and disengaged. That’s a tell. When identity is involved, people stop arguing substance and start contesting whether evidence is allowed to count yet.

Now let’s talk about evidence, using sources who are not selling LLMs, not building them, and not financially dependent on hype.

Martin Fowler has explicitly written about AI-assisted development changing how code is produced, reviewed, and maintained, noting that large portions of what used to be hands-on programmer labor are being absorbed by tools. His framing is cautious, but clear: AI is collapsing layers of work, not merely speeding up typing. That is labor substitution at the task level.

Kent Beck, one of the most conservative voices in software engineering, has publicly stated that AI pair-programming fundamentally changes how much code a single developer can responsibly produce, and that this alters team dynamics and staffing assumptions. Beck is not bullish by temperament. When he says the workflow has changed, he means it.

Bjarne Stroustrup has explicitly acknowledged that AI-assisted code generation changes the economics of programming by automating work that previously required skilled human attention, while also warning about misuse. The warning matters, but the admission matters more: the work is being automated.

Microsoft Research, which is structurally separated from product marketing, has published peer-reviewed studies showing that developers using AI coding assistants complete tasks significantly faster and with lower cognitive load. These papers are not written by executives. They are written by researchers whose credibility depends on methodological restraint, not hype.

GitHub Copilot’s controlled studies, authored with external researchers, show measurable increases in task completion speed, reduced time-to-first-solution, and increased throughput. You can argue about long-term quality. You cannot argue “no evidence” without pretending these studies don’t exist.

Then there is plain, boring observation.

AI-assisted coding is directly eliminating discrete units of programmer labor: boilerplate, CRUD endpoints, test scaffolding, migrations, refactors, first drafts, glue code. These were not side chores. They were how junior and mid-level engineers justified headcount. That work is disappearing as a category, which is why junior hiring is down and why backfills quietly don’t happen.

You don’t need mass layoffs to identify a structural shift. Structural change shows up first in roles that stop being hired, positions that don’t get replaced, and how much one person can ship. Waiting for headline employment numbers before acknowledging the trend is mistaking lagging indicators for evidence.

If you want to argue that AI-assisted coding will not compress labor this time, that’s a valid position. But then you need to explain why higher individual leverage won’t reduce team size. Why faster idea-to-code cycles won’t eliminate roles. Why organizations will keep paying for surplus engineering labor when fewer people can deliver the same output.

But “there is no evidence” isn’t a counterargument. It’s denial wearing the aesthetic of rigor.

I treated it with the amount of seriousness it deserves, and provided exactly as much evidence as you did lol. It's on you to prove your statement, not on me to disprove you.

Also, you still haven't provided the kind of evidence you say is necessary. None of the "evidence" you listed is actually evidence of mass change in engineering.

> AI-assisted coding is directly eliminating discrete units of programmer labor: boilerplate, CRUD endpoints, test scaffolding, migrations, refactors, first drafts, glue code.

You are not a professional engineer lol, because most of those things are already automated and have been for decades. What on earth do you think we do every day?

Also, saying “this has been automated for decades” is only persuasive if those automations ever removed headcount. They didn’t. This does. Quietly. At the margin. That’s why you’re arguing semantics instead of metrics.

And the “you’re not a professional engineer” line is pure tell. People reach for status policing when the substance gets uncomfortable. If the work were as untouched as you imply, there’d be no need to defend it this hard.

And sure it did. We don't have test engineers or QA nearly as much as we used to, and a lot of IT work is automated, too.

Do you think we sit around, artisinally crafting code the slow way, or something?

Personally I think being a swe is easy. It’s one of the easiest “engineering” skills you can learn hence why you have tons of people learning by themselves or from boot camps while other engineering fields require much more rigor and training to be successful. There’s no bootcamp to be a rocket engineer and that’s literally the difference.

The confidence you have here and how completely off base you are with your intuition on who is just evidence for how wrong you are everywhere else. You should take that to heart. Everything we are talking about is speculation, but your idiotic statements about me is on the ground evidence for how wrong you can be. Why would anyone trust your speculation about AI by how wildly wrong you are “clocking” me in.

> Do you think we sit around, artisinally crafting code the slow way, or something?

This statement is just dripping with raw arrogance. It’s insane, it just shows you think you’re better than everyone because you’re a swe. Let me get one thing straight, I’m a swe with tons of experience (likely more than you) and I’m proud of my technical knowledge and depth, but do I think that other “non swes” just look at us as if we are artisans? That’s some next level narcissism. It’s a fucking job role bro, we’re not “artisans” and nobody thinks of us that way, get off your high horse.

Also wtf do you mean by the “slow” way? Do you have communication issues? Not only will a non swe not understand you but even a swe doesn’t have a clue what the “slow” way means.

>We don't have test engineers or QA nearly as much as we used to, and a lot of IT work is automated, too.

Oh like automated testing or infra as code?? Ooooh such a great engineer you are for knowing these unknowable things that any idiot can learn. Thanks for letting me know a lot of IT work is “automated.” This area is one of the most mundane areas of software engineering, a bunch of rote procedures and best practices.

Also your “my dude” comments everywhere make you look not as smart as you probably think you look. Just some advice for you.

Good day to you sir.

Another lesson history has taught us though, is that people don't defend narratives, they defend status. Not always successfully. They might not update beliefs, but they act effectively, decisively and sometimes brutally to protect status. You're making an evolutionary biology argument (which is always shady!) but people see loss of status as an existential threat, and they react with anger, not just denial.

This seems extreme and obviously incorrect.