[regularfry]

The bottleneck has moved from producing a thing that works to knowing that the thing was the right thing to build. The more of the latter they can take on, the fewer knowledge workers are needed at all. So rather than 5% of every knowledge worker's salary going into tokens, 100% of the knowledge worker's total employment cost goes into tokens and you get a 20x productivity boost as a theoretical minimum across those tasks.

That's the game. There's a view you could take of this that this is just a growing of the pie: with those cost dynamics a lot more "small businesses" get a vast amount of leverage, so the overall economy grows without replacing the knowledge workers. I'm not sure I trust the MBA class to have that view.

[seanp2k2]

>The bottleneck has moved from producing a thing that works to knowing that the thing was the right thing to build

I would argue that that's been the case for quite some time before AI. As an example, what innovative amazing world-changing products have Google or Meta launched in the past decade with their very high numbers of very talented and highly-compensated engineers? The issue with most big tech companies are leadership, strategy, and product direction. I'm not saying that they don't make any profits, just that they probably aren't "building [the right thing]".

AI for product development and management would be far more impactful than automating rote coding tasks / building React UIs that mirror API structures IMO.

[Figs]

> AI for product development and management would be far more impactful than automating rote coding tasks [...]

Yeah, if this stuff actually worked that well already, OpenAI et al. would just run AI CEOs and engineers. Why get some other company to pay you at all when you can automate every other company out of existence and take all the money they make?

The fact of the matter is that while the tech has some uses, it sure as hell isn't a full scale replacement and you almost always actually have to massage the input into LLMs to get anything decent back out in practice. Some CEOs and managers can learn to do this, of course, and some already are... but that quickly turns into a second full time job. A "programmer" is still needed. The job might change from mostly hand-writing C++/JS/Python to prompt engineering + some manual coding to fix all the stupid fuck-ups that the bots can't solve themselves, but you still need someone to actually prompt the bot.

When that changes, it won't just be engineers losing work; there will be no reason to even have a human CEO any more.

[dogwalker5000]

> When that changes, it won't just be engineers losing work; there will be no reason to even have a human CEO any more.

The human race isn’t ready for that world IMHO. The only reason there is a middle class is because people have leverage in the form of their labor. When that becomes worthless … the people who own stuff and make their living from doing so won’t hesitate to get rid of everyone else - whom are now worthless to them.

[whattheheckheck]

Humans will revolt and mutiny on the ai ceo so fast its not even funny

[thejazzman]

https://abcnews.com/US/man-allegedly-throws-molotov-cocktail...

[ares623]

Imagine being deluded enough that you, a CEO, can continue to go buy groceries and drink at a cafe relaxing in that future

[aspenmartin]

I don't know, if you've ever tried to build something at companies of that scale you run into incredibly boring problems "what data table do I need for X" and "who is the right person to reach out to for Y" and "they aren't answering me I guess I'll have to escalate"

I don't think there is any shortage of great ideas at these companies, they are just extremely bloated. And I don't think its something like indecision or bad PMs, it's "we have a finite amount of time and resources so we need to be conservative but also not too conservative"

If you have AI systems that can simply build out POCs in days, backtest on real data, show reliable results and numbers, you get a suite of product options you were never able to get before. If you have coding agents that can speed up implementation, you can build more stuff and choose the things that stick.

It changes the cost/benefit calculus of the entire business. I think you are exactly right in that: PMs/leadership are by their nature orchestration machines. Other roles are as well, but I think PM's are at a particular advantage here in that it will be quite awhile I would expect before core product decisions and creativity can be delegated to an AI, but not quite awhile until virtually everything that they're blocked on (legal approvals, POCs, wire frames, etc etc etc) will become less and less of a blocker

[supern0va]

>If you have AI systems that can simply build out POCs in days, backtest on real data, show reliable results and numbers, you get a suite of product options you were never able to get before. If you have coding agents that can speed up implementation, you can build more stuff and choose the things that stick.

I'll also add this: within a large organization, you often need to interact with many different codebases owned by many different teams. Agents have made it much easier to wrangle by having the ability to deploy one to scope out your web of dependencies to learn about what would be needed for feature X, and how that integration can happen.

We've been doing far more away team work simply because it makes things move faster. It's easier to convince a team to sign off/review something than it is to get them to commit to the planning and eventual work.

It genuinely is helping things move faster inside large organizations. Or at least, it is for us, particularly since we're getting organizational prioritization to actually build the scaffolding to make those agents more effective at search.

[aspenmartin]

> It's easier to convince a team to sign off/review something than it is to get them to commit to the planning and eventual work.

1000x yes: you have touched on what I think is the single biggest factor here, that is the humongous value of POCs. they are gnarly to build without agents, and so we used to have to get everyone on board so we didn't get screwed in performance reviews, which was monumental task because that means convincing very busy PMs who have a lot on their plate and dont want to take risks on things they don't understand, and now it's like "can we scale this out" and you have a very nicely formatted proposal and POC. It de-risks things very quickly

[skydhash]

Pieces of concept and other prototypes have always been cheap (see hackatons). The main issue is that as soon as you’re touching customer data or modifying process they’ve paid you for, you have to be really careful. No one wants to be responsible for an outage that cost the company its biggest customer.

[aspenmartin]

Yes, but at scaled companies, where building a simple POC hooked into real systems is nowhere close to easy. To the point where it means that you might as well just do the full thing. That's where the enterprise spend and the impact is.

[skydhash]

Isn’t that a matter of configuration management? Or do you want to alter the real systems as well?

[aspenmartin]

historically it's been a matter of an absolutely horrific amount of Kafka-esque problems.

Say I want to build a feature in a product.

- DS has to do a deep dive (need buy in) to opportunity size and derisk with data. That DS has to work with other DS (people may have left or moved teams) to figure out how to get the right data and figure out what the difference is between 10 different tables that have overlapping but inconsistent data. - Eng has to build up an actual simple demo (need buy in) - Design has to make it not hideous (need buy in) - Legal has to review what you're doing; POCs should involve real data where possible because otherwise no one will trust it, even if its just for user analysis on existing products

This plus about 6 internal system bugs for custom tools that are flaky and who's team has long been re-orged or laid off, 8 people who won't answer you, 2 PTO's for the stakeholders, 6 weekly meetings

no one did POCs, they just had ideas and tried to get PM's to put it on the roadmap so if it fell through at least it was bought into

[jimbokun]

Legal approvals won’t be in that category.

You still want someone whose ass is on the line if they get it wrong.

[aspenmartin]

Absolutely but you want to package it to them nicely and efficiently. The biggest blocker is legal and everyone else speak two completely different languages and we often don’t know what’s important to flag and legal doesn’t know enough to ask all the right questions. Also, many things can be templated, and in an industry where regulations and precedents change so quickly, agents are at the very least a good tool to flag issues (e.g. we were approved to use data X for Y but now decision Z negates this). The propagation of this information is not very effective now and legal review at tech companies, while absolutely essential, is somehow a worse experience than going to the DMV when it’s crowded.

[regularfry]

Yes, that exists at the wider business level. No question. I think what needs to get asked is are we talking about a bottleneck within the business as a whole, or a bottleneck within the scope of the knowledge work in question. Within software delivery there's a very clear shift when it's suddenly trivial to drop a 100kLoC plausible-looking PR into code review within an afternoon. Producing working code with a whole bunch of tests which make a very clear assertion that it does, in fact, work has had (if you're going that way) all the human-scale thinking time taken out of it, down to a rounding error. It still needs to be checked by a human, which was previously assumed to be a comparatively quick task in comparison to producing the thing. At least, it does where I am, and I don't think that's a silly position today at all.

If they can crack that latter review/spec-check/assurance step, checking that what was built was what was demanded of the problem such that we don't have humans in the loop at that step either, then the bottleneck moves again. Then I think it moves to requirements capture and to product development, but that might depend on the industry.

[fragmede]

Trusting CodeRabbit for sign-off is "just" a small matter of configuration.

[regularfry]

And convincing your org that such a thing is safe to do, which is decidedly not.

[nilamo]

> As an example, what innovative amazing world-changing products have Google or Meta launched in the past decade

Kubernetes is at 11 years ago, and is huge enough to be included there. The Google Pixel was just under 10 years ago. So... not nothing haha

[rogerrogerr]

Numbers I see put Pixel at less than 5% of iPhone sales. Not nothing, but world-changing? I doubt the world would look significantly different had Google not done Pixel.

[nonethewiser]

>I would argue that that's been the case for quite some time before AI.

I would agree but it's really minimized the building. More and more time is being spent on pre-coding work.

[zjaffee]

If you really think this you simply have no theory of mind for this stuff. There are tons of immensely successful products in the ad space that both of those companies have launched. They don't need to innovate in the product or technology space (doing so certainly makes a big difference in having more placement for ad real estate), but to suggest there have been no real innovations (specifically engineering specific innovations) related to ad tech would be completely ridiculous to suggest. You don't need to change the world to get rich, just look at wall street where major innovations have been made in the pricing models of fixed income securities.

Second to this are countless other areas that have a major impact on the companies bottom line that are entirely engineering driven, especially at google given they are a cloud provider and have meaningfully grown the workspace business and launched waymo in this time.

[nostrademons]

Google's internally developed and sometimes even launched plenty of innovative new products in the past decade. Stadia, Fuchsia, federated learning, and the whole transformer architecture that underlies this AI boom are good examples.

The problem is they get killed by some other executive who is afraid of their department looking bad by comparison.

I think this is fairly illustrative of the challenges in AI becoming as impactful as the Internet. The bottleneck is not making things. There are plenty of people who are really good at making things and can easily be 10x or 100x as productive as the average corporate worker. YCombinator was founded on that premise - small teams of founders and early employees could be orders of magnitudes more productive than the 1000s of corporate employees at their competitors.

The bottleneck is on bringing your product to market. If your innovative new product is built within a corporate environment, it'll get killed unless the executive you work under can get a promotion out of it, and you'll be denied all sorts of help with approvals, launch process, PR, marketing, branding, etc. If it's a startup, they'll try to shut you out with exclusive distribution deals, legal threats, lobbying efforts to change the legal environment, PR campaigns, FUD, etc.

The Internet was revolutionary because it let millions of people bring products to market without asking permission. Instead of having to bid for retail shelf space among dozens of entrenched competitors that all had sweetheart deals with the retailer, you could just put up a website and sell it to anyone across the globe. Instead of following hundreds of regulations that governed existing commerce, you could just launch something and sort it out later. AI doesn't really have that property - if anything, it makes things more centralized, with more gatekeepers, and so seems more likely to destroy economic value than add to it.

[Danox]

Google does not follow through in the long run on many of their pet me-too follow projects, however they do not stray away from their core remit making their real customers happy the ones who buy the ads…

Obviously that includes whatever needs to be done to hoover in data from their marks and Meta also does the same thing without fail and both are really good at it. But outside their remit not so much.

[regularfry]

What I think is happening is that the scale of thing you can hope to build at a below-corporate scale should radically grow. Corporate environments should suffer for this, being that inefficient.

> YCombinator was founded on that premise - small teams of founders and early employees could be orders of magnitudes more productive than the 1000s of corporate employees at their competitors.

I think this is still true, but the theory is:

1. You don't need YC-type funding to do YC-type business any more; 2. You don't need to scale the business past those small teams any more, you just buy more tokens.

For clarity YC still obviously has a place as an incubator, mentoring, and networking function. I just think that what was previously the inevitable conclusion that you have to hire all the people the second you hit PMF to keep up with scaling the business as you scale sales is no longer inevitable. If you didn't want to go that way before AI, you were a "lifestyle business" and not worth investing in. As more and more knowledge functions get capably implemented by AI, it's the preferred position: humans are vastly more expensive than tokens, so you want them doing the stuff the AI still can't do.

I don't think this necessarily translates to mass unemployment. I think it translates to masses of smaller businesses that are radically more efficient because the handoffs between business functions are tool calls, not emails to someone who doesn't want to help.

> The Internet was revolutionary because it let millions of people bring products to market without asking permission.

Think about it this way: if I am a small business owner but I think it makes sense to do something that previously only a team in a corporate environment could do but is now within the reach of AI, not only can I do it now, but I also don't have to ask anyone for permission! Who wins between the corporation and the small business in that scenario?

> AI doesn't really have that property - if anything, it makes things more centralized, with more gatekeepers, and so seems more likely to destroy economic value than add to it.

I think this will turn out to be backwards. I can see a version of this where the number of things you can do without needing to turn to a gatekeeper for help increases to the extent that the balance completely inverts.

The vast majority of businesses are small, and AI can give them tools which previously required corporate scale to make sense, without the inefficient hand-offs between busy, political humans. Which is also something that the internet did! Getting an advert in front of a national market pre-internet was Hard but sometimes you had to do it because your target market was "all Canadians who buy toothpaste" or whatever and that meant saturation-bombing the physical environment with physical billboard ads, posters, flyers, and so on. So you only did it if you were P&G-scale. Now you, personally, can do it, trivially, for better or worse.

[nostrademons]

I dunno if the employees were ever really needed for scale. WhatsApp famously had 300M users and 13 employees at the time of acquisition; Instagram was something like 50M users and 55 employees. If you know what you're doing software scales basically infinitely, and the employees are there to make the software just slightly more tailored to specific user populations (and because upward career mobility for managers involves having more headcount). Yeah, building a revenue model takes people, but Valve employs only about 400 people and makes billions, as do various quant hedge funds like DE Shaw or RenTech.

[regularfry]

The insta/whatsapp/plentyoffish model works if you're very lucky with both product-market fit and the technical constraints of the product itself. If you have something that technically scales extremely cleanly, it basically sells itself, and it doesn't need feature churn to retain or gain users, you're golden. I do think more businesses could do with checking whether they do in fact have that lottery ticket before hitting the scale button; there aren't that many examples around.

> Valve

Arguably a monopoly. They've got a product that sells itself with very low infra overheads for the income.

> Hedge funds

Very different model. I don't think the same intuitions apply.

[Danox]

Most of the people they have on staff are there to support their real customers, and I don’t mean the marks out in Internet land Google and Meta‘s real customers are the people placing ads and giving them money, most of the staff is dedicated towards servicing them, that again is where most of the money goes to support their real customers.

[beambot]

Google & Meta are illustrative of late-stage capitalism -- it's all about distribution, not innovation. Their job is (mostly) to just acquire the products that have passed the gauntlet, then scale up their monetization through their distribution-focused machine. The same dynamic plays out in virtually every industry (not just tech).

You'll find that most internal "innovation" teams are just lip service. In most cases, the "mothership" will be incapable of reproducing true innovation -- from a statistical perspective, culture perspective (mega corps are anti-scrappy; internal politics), and motivation perspective (startups aren't 9-to-5). It's much easier to have big M&A budgets, a VC arm, and some handwavvy internal innovation group.

Every now and again, you'll get real innovations (Waymo, transistors, GUIs), but even those have a spotty track record of commercialization when created internally.

[fragmede]

The one I'd point out for that list is Kodak and the digital camera.

[cogman10]

This is the same argument that has been historically made for outsourcing developers. Get 20 more devs for the cost of 1 dev in the US.

I suspect that AI will fail to pan out to the same extent for the same reason why outsourcing hasn't fully panned out (even though every company tries it after getting big enough).

The problems that will come up will be and always have been ongoing maintenance. AI is great at writing new code without a brain behind it, but once you get to the point where you need to refactor code, you start really needing someone with coding experience to guide the AI or veto it's mistakes.

I don't think that's really fixable even with a lot better AI. It's not something that ultimately comes out of the likes of github data.

I'm not saying that AI isn't going to make things better, btw, I just don't think we'll see a 20x improvement. Probably more like 1.5 or 2x.

[roncesvalles]

Outsourcing of knowledge workers didn't work out because at large enough scales, the geographic arbitrage disappeared. Companies mostly always got what they paid for.

The determinant of success was only whether the task needed American-tier labor or could make do with sub-American quality labor.

[m1coti]

I am not sure this feels right. I agree that the US currently has leading minds in terms of tech, but I am not sure it is too big of difference with the EU knowledge workers. EU is still a lot cheaper then US in terms of wages you would need to pay.

[outside1234]

EU workers themselves get a lot less, but the EU is expensive because of 1) the huge payroll tax (45% in France) and 2) the challenges with hiring and firing mean you are carrying people that aren’t contributing.

[roncesvalles]

EU doesn't have the scale. There are probably more SWEs in one little town in the Bay Area than entire European countries.

Also, many European devs simply move to the US. Immigration is the primary means by which the arbitrage disappears.

[irishcoffee]

Sure is an interesting thought. None of this is sarcasm: why do US companies deal with the time zone differences and language barriers they won’t need to bother with so much by outsourcing to say, Ireland?

[regularfry]

The mechanism is often that they'll actually outsource to someone like Accenture, who have teams everywhere, and whose contract managers will try to get their cheapest viable team onto the contract to maximise their margin. If the buyer can't judge the quality of what they're buying, or doesn't know why the resulting hand-offs, delays, mistakes and rework will cost them more than keeping everything in-house ever would have, they're going to have a bad time.

[surgical_fire]

Er, US companies do outsource to Ireland.

Basically every big tech has large offices and employ a lot of people there.

The limitation is that Ireland is a relatively small country, and most Irish developers are already employed (which is why Ireland end up being one of the main destinations for tech workers being hired from abroad).

[lmm]

Ireland isn't that much cheaper than, say, Oklahoma. And the cultural differences with Ireland are not a lot smaller than those with India or the Philippines or what have you, once you try to actually start working together.

(Yes, all the good developers from Oklahoma move out, but the same is true of Ireland)

[cogman10]

That's certainly part of it. But the other part that I've heard time and time again is that in order for outsourcing to be successful you basically needed an american engineer in the mix hand holding everything, clarifying requirements, and vetoing bad code.

That part of dev work, the requirements gathering, attention to details, clarifying requirements, is something AI also struggles with. A lot of companies basically waste time and money on outsourced devs because without a clear path forward they effectively will sit and do nothing, waiting for a prompt.

[m1coti]

I would not agree on that point. It really depends on company's structure. I mean it also depends with people that makes the team. I would say there are a lot of unknowns but I would certainly not generalize.

How I find your argument is that one distinguished engineer from US could do the same with the use of AI.

I worked with both and I know great and bad engineers from both sides. Only thing is that US has a bigger pool of great engineers.

[regularfry]

I think the mechanism here isn't that American engineers are magic. It's that you need that contextual knowledge really close to where the work is actually being done, so that the turnaround for questions, blockages, clarifications, "we've got no work to do", quality level-setting and so on is on the scale of minutes, not time-zones.

[jimbokun]

It doesn’t have to be an American but it does have to be a direct employee of the company ideally working in the same time zone as management and the people defining the requirements.

[asdff]

Outsourcing of knowledge workers is still ramping up. The issue in the past was the skills were few and far between internationally. Facilities were also not built. That has changed now in a lot of fields. New campuses have been built in places like Bangalore and Hyderabad, even Singapore. The skills are there now, the training is decent, and you can see that the hiring is going on for very skilled titles in these cities. It is a different animal than just 10 years ago in this.

[jimbokun]

The “American tier” labor of course is distributed across the world and the top performers in every nation find ways to get paid at something approaching American salary levels. Look at all the international FAANG offices paying high salaries, in purchase pricing parity terms.

[regularfry]

> I suspect that AI will fail to pan out to the same extent for the same reason why outsourcing hasn't fully panned out

My mental model for that is that outsourcing fails where the work is being done organisationally far from the knowledge needed to do it. We know that's true of teams inside organisations, there's been a lot of research on how distance in the organisational tree negatively impacts productivity. Outsourcing is a pathological worst-case of that.

The promise (promise! We're not there yet!) of AI is that I can have a cross-functional team on my laptop. Organisational distance is zero. Where previously the outsourced team has to wait for the time zones to roll round so I can answer their blocking question when I get to my email STRICTLY AFTER I have had my coffee, now it's a prompt in a chat window with a button I can click to make a choice in 5 seconds. Delay is gone, cost of delay is gone.

> The problems that will come up will be and always have been ongoing maintenance. AI is great at writing new code without a brain behind it, but once you get to the point where you need to refactor code, you start really needing someone with coding experience to guide the AI or veto it's mistakes.

Oh, absolutely. That's a minefield. Today. It will be, right up until it isn't. There are ways to set up agents and projects right now that make a dramatic difference to how this part of the picture plays out, but those will sink into the harnesses as time goes on.

But also the big problem with maintenance and outsourced teams tends to be the commercial structure around the contract. You get a Build team, who Build the Thing and then: no more features for you, anything you want to add past the original spec costs extra. They hand over to the Run And Maintain team, who get to fix all the bugs that the Build team left but without the knowledge gained from building the thing, but are scaled and located to be absolutely as cheap as the supplier can get away with so probably don't have the skill, inclination, motivation, or permission to take on any restructuring to make the bug fixing easier and they're on the wrong end of the globe so there's a 24-hour latency on any queries. It's a terrible way to set teams up, but it looks good on paper.

Again, that's peculiar to outsourcing and completely goes away if I have the same team that built the thing own the thing long-term. That's true if it's humans or AI!

> I don't think that's really fixable even with a lot better AI. It's not something that ultimately comes out of the likes of github data.

No, it's a harness problem. You need to start from a maintainable point and keep standards in place. It'll take work to get the harnesses there and it's not ubiquitous. You might also need better models, but I've already personally seen big differences in outcomes between projects that took certain steps and others that didn't; it's nothing revolutionary, mostly stuff that works for humans also works for AIs but you need to know to ask for it.

> I'm not saying that AI isn't going to make things better, btw, I just don't think we'll see a 20x improvement. Probably more like 1.5 or 2x.

I think people radically underestimate the cost of delay. I don't know if 20x is realistic for the AI itself, but I think it's not impossible once the inefficiencies of having to go to other humans is factored in.

[omcnoe]

Outsourcing also fails because it’s a pathological case of adverse selection. The businesses that outsource projects are ones who are organisationally incapable of managing those projects well internally. But, that inability extends to their oversight of outsourcing shops as well.

End result is that many outsourcing firms are borderline fraudulent in the way they treat their customers.

[bethekind]

> mostly stuff that works for humans also works for AIs but you need to know to ask for it

I'm most curious about this sentence. What have you noticed about the similarities? I'm getting really good at asking for confidence levels, tests and pushing back, but I'm curious what you found

[regularfry]

If you don't start with a clear file structure and code architecture appropriate to your problem domain, the agent won't fill in the gaps and will give you mush that it will eventually fail to navigate effectively. So you need to be explicit and say (e.g.) "this project is structured as a Ports And Adapters project, one class per file. Adapters go in src/adapters, core domain in src/core/app, ports in src/core/ports, entry points in src/main" in AGENTS.md. Picking something like that rather than free-handing the structure also helps humans enormously, that's why those ideas exist. I've found that doing something like that helps the agents to stop the code from creeping into mush over time, and actually gives them a reason to self-correct drift if it happens. I tend to prefer something off the shelf like Hexagonal Architecture because the chances are good that the agent already knows about it and has a lot of background on it, but has no reason to pick it amongst all the alternatives unless prompted.

Tests are non-negotiable. I've found it helps to be very explicit about Red-Green-Refactor loops so you don't get it trying to one-shot more than it should, alongside git pre-commit hooks that won't let failing tests accidentally get committed. Again, this helps humans.

[extraextra]

Thanks for that

I'm starting my first coding project with Claude Code and your comment gave me some helpful topics to study

[layer8]

Who pays for that value, and from what, if all knowledge workers lose their jobs?

It sounds like the economy would largely reduce to the small minority class of independently wealthy people.

[simonw]

The more time I spend using agent tools the less I worry about knowledge worker job loss.

It takes a skilled knowledge worker to use these things.

[keeda]

Yes, but I do worry about junior knowledge worker job loss. These models are very good (and getting better) at the vast dark matter of "donkey work" that happens in knowledge-based industries -- work typically done by junior devs / analysts / lawyers / consultants, paralegals, admin assistants, customer success / support, etc. -- and those roles comprise the bulk of the workforce.

And worse, these are the tasks that help the junior people eventually grow into the skilled knowledge workers required to operate models, so there's a pipeline problem too.

[simplyluke]

I do too, but I think it currently has a lot more to do with the quasi-recession we've been in since the end of ZIRP and AI is a better excuse to stop training juniors than telling investors it's belt tightening, just like layoffs.

I'm already seeing tech execs/hiring managers getting very frustrated at the lack of new-senior-engineers to hire. The market will correct for this in time.

[rogerrogerr]

Curious if you can share any backing information from your last statement? As a senior engineer (well, that's my job title anyway), I find it encouraging.

[simplyluke]

This doesn't break it down by experience, and I can't find specific data on that, but the recent spike in demand for engineers + subsequent drop in unemployment this year is well documented [1].

The demand for senior+ engineers has remained steadier through this downturn from my anecdotal observations, with new grads being by far the most negatively affected, but even that seems to both be shifting from talking to people a handful of years younger than me + CS enrollment has already precipitously declined [2] as the narrative that programming is dead because of AI has spread rapidly.

All that leads me to think it's going to be a junk-show over the next decade for people trying to hire as the pipeline was destroyed.

1: https://www.citadelsecurities.com/news-and-insights/2026-glo... 2: https://www.washingtonpost.com/technology/2026/04/13/compute...

[kansface]

We'll get around to training job specific models or the equivalent. Thats just lower on the value chain for now.

[layer8]

Sure. I was challenging the parent on how the “game” they are positing would play out.

[regularfry]

See https://news.ycombinator.com/item?id=48300427 for an alternative take. I don't think either direction is inevitable, yet.

To follow on from that comment, if the growth in breadth of capacity of AI leads to a decrease in the risk of running a smaller business, which I don't think is an unreasonable prediction, then it's not inevitable people do lose their jobs. Employers get smaller, higher-leverage, and more plentiful.

[whatshisface]

There were no knowledge workers in the middle ages.

[wongarsu]

Back then people were mostly farmers, but we already automated that job away.

Not completely, but compared to the middle ages we 50x'd their output. Which is a great illustration what it means to make a job 50 times more productive. We went from 80-90% of the population being required to barely make enough food for everyone to survive, to 4% of the population producing such an abundance that consuming too much food has become a systemic health issue

[fodkodrasz]

At the mere cost of destroying soil, and polluting water and the atmosphere in only 200 years! Possibly this will also play out well, and there is a huge market of... maybe social media influencer economy to pick up those being automated out of their previous work... or rather identity, as actually much like in the middle ages, the modern world also makes the profession largely the identity of the individual.

I'm pretty skeptical on the outcomes and the costs also (natural and social as well), but possibly we can have 50x or even more software in the end! The phrase will be truer than ever:

> Software is eating the world!

[coryrc]

Maybe ironically, but software and robotics should allow us to scale regenerative agriculture in a way that doesn't leave everyone in poverty. We already have lasers mounted to trailers doing precise weeding instead of broad herbicide usage.

https://www.agtechmarket.net/news/laserweeding (random web search, I don't vouch for this site, it just looks legit at a glance)

Next innovation could be to scale succession planting, which keeps the ground from being exposed in between crops and lets you transition from nitrogen fixers to users quicker, getting more food out per acre while reducing fertilizer usage. But you can't do that with current harvesters and human labor is too valuable to spend on this.

Also take broccoli harvesting, typically you get a few big heads, then it keeps producing smaller heads, but it's not economical to harvest the smaller heads with human labor. Robotic harvesting lets the same plant produce more food per acre and uses the energy needed for new plants instead to keep producing food.

[fodkodrasz]

Masses will be unemployed, due to robots displacing them, but human labor will also be too costly. We won't be able to afford a person shepherding, but we will need to produce "meat" (substitutes) in plants, or in inhumane animal-jail, and we'll need robot-weedkiller lasers to produce the feedstock instead of letting animals graze... and we'll give the food produced this way to people on UBI...

This is where this is going, the whole industrialism is totally self-serving, and for every problem its answer is digging deeper in the rabbit hole, and creating 2 more problems in addition to solving the initial problem only half-way.

I don't want to say what you are suggesting is not possibly useful, I just want to emphasize how stuff works out in reality, in addition to doing some nice stuff like what you called out (the halfway solution to the problems). All we get is more alienation and humans getting depressed and feeling a lack of purpose... but somehow we cannot afford to pay fair prices for the agricultural work, and pay fair prices for the food, and not overproduce and overpollute... and the same thing is happening in every aspect of the human condition, not only food production, which is the most basic and ancient activity we have been doing.

[bryanlarsen]

Farming has been destroying soil and polluting water for thousands of years. The Tigris & Euphrates used to be crazy fertile, now it's desert. Yes, the destruction has accelerated but farms now feed 8 billion people.

[fodkodrasz]

We need to go faster! We need more people, and more machines, so we can go even faster!

This also leads to a kind of a singularity.

[thewebguyd]

There definitely were what could be considered knowledge workers in the (high) middle ages, it just wasn't the majority of work like today. The knowledge workers then were just a tiny, elite faction, mostly employed by the church or directly by nobility. Kindgoms were still big bureaucracies and needed scribes, theologians, academics, lawyers.

[jrochkind1]

Relatively few anyway. Monks (who wrote and edited books and managed libraries, and also taught), artists and musicians, bookkeepers/treasury/exchequer, scribes/chancery (who were the administrators of the kingdoms), and bankers all existed in European "middle ages". But a significantly smaller part of economy/society compared to "western world" now, yes.

[skydhash]

Are you sure? Any functional organization requires keepers to oil the machine. First the government. The best examples were the chinese empire, the catholic church, and the various kingdoms. Or do you think that everyone was either fighting or farming? Stewardship is knowledge work. Bookkeeping is another.

[layer8]

There wasn’t 20x value to pay for in the middle ages either.

[rvz]

> Who pays for that value, and from what, if all knowledge workers lose their jobs?

They do not care unless these companies can get a bailout.

UBI only exists for companies that are too big to fail. Case in point, 2008 and SVB when there was too much money on the line.

One of the AI companies attempted to guarantee themselves a way for the government to bail them out if they were close to defaulting on the debt from the data center build out.

[mikeocool]

SVB didn't get bailed out, their investors and creditors were wiped out. You could argue depositors were bailed out -- as they took the undue risk of keeping more than $250k in a single bank (though as part of a requirement for getting a loan from SVB, you had to have your operating accounts with them. So lots of companies had no choice, as SVB was one of the few banks that would lend to them).

Arguably, the main impact of securing SVB depositors above the $250k limit is that it prevented thousands of people from being laid off that week, as their employers wouldn't have had the money to make payroll the following Wednesday.

[matwood]

Thank you for saying this. Continuing to point at SVB as a bailout is annoying. They were not bailed out. Anyone with deposits in an accredited bank should be made whole - always. Without trusted banking we have no economy.

[anonymars]

> Anyone with deposits in an accredited bank should be made whole - always

Sure, but is that the case now? Is everyone made whole when a bank fails and they have more deposits than the insurance limits? Or only when it's the well-connected / too-big-to-fail?

Looks like the answer is no: https://www.wsj.com/finance/banking/a-small-banks-failure-le...

So I don't think it's unreasonable to describe SVB as a bailout. Not for the investors, but for the depositors. Has anything changed to reduce the moral hazard / make it less likely to recur?

[rvz]

So we all now know that a bailout DID occur with the SVB depositors who had all their money in the bank and most deposits were over the FDIC insurance limit. The FDIC insurance rules somehow didn't apply here because there was too much money at risk. (And too big to fail).

But if there was a bank failure at a regionally smaller bank with a regular customer or startup depositing the same amount of money over the insurance limit, their money is gone.

Just like Intel got a "bailout" from investment as chosen by the US government, AI will eventually have a very similar story.

[matwood]

> Sure, but is that the case now?

Pretty much and has been for awhile.

https://nyulawreview.org/wp-content/uploads/2025/05/100-NYU-...

In early 2023, within the span of two months, the United States experienced three out of the four largest commercial bank failures in U.S. history, as Signature Bank, Silicon Valley Bank, and First Republic Bank all toppled.1 Yet, despite these banks having roughly $300 billion in uninsured deposits at the time of their failures2 and despite the failures costing the Deposit Insurance Fund (DIF) of the Federal Deposit Insurance Corporation (FDIC) an estimated $38 billion, uninsured depositors took no losses in any of the failures.3 While these results were striking, they were far from unusual. Since 2008, uninsured depositors have experienced losses in only 6% of total U.S. bank failures.

...

Formally, the United States caps deposit insurance at $250,000 per account,6 but, in reality, the post-2008 financial system comes close to providing de facto total deposit insurance covering all amounts in all accounts.

[fragmede]

> UBI only exists for companies

What's the U stand for in UBI?

[kmac_]

Producing a thing has always been cheap since personal computers existed. From mail-order software companies' times to SaaS times, producing a sellable MVP was an initial cost that is relatively small compared to the later cost of expansion and maintenance. Marketing and selling was and still is the hardest part.

[roncesvalles]

Why do you think of knowledge workers as a fungible commodity?

What makes you think the people who used to build (or would have built) software will switch into the industry of "knowing that the thing was the right thing to build", as opposed to something cooler like surgery, city planning or experimental physics? The roles within a tech company are not the only jobs in the world.

[regularfry]

> Why do you think of knowledge workers as a fungible commodity?

I don't.

> What makes you think the people who used to build (or would have built) software will switch into the industry of "knowing that the thing was the right thing to build", as opposed to something cooler like surgery, city planning or experimental physics?

Because it's probably already part of the job. It's a change of emphasis, not a change of career. Your boss can already ask you to do it. If you're producing code, you're probably also reviewing code, checking it matches the acceptance criteria, testing it, sanity checking that it was the right code to have been written, today.

[OtherShrezzing]

> The bottleneck has moved from producing a thing that works to knowing that the thing was the right thing to build

“There’s more capital than good ideas to fund” has been a complaint from the likes of A16z & other VCs for a long time now. It’s why we ended up with stuff like NFTs getting funded.

[radicaldreamer]

If knowledge workers get laid off in mass, you can expect political curbs on AI adoption.

[jimbokun]

That’s very unimpressive return on investment compared to what was promised.

[regularfry]

I have nothing riding on any specific multiple. Choose your own adventure there.