The tech market is fundamentally fucked up and AI is just a scapegoat | Hacker News Reader

The tech market is fundamentally fucked up and AI is just a scapegoat

bayramovanar.substack.com

313 pointsBayramovanar220 comments

>In traditional industries like manufacturing you don’t hire 500 factory workers unless you have a production line that needs them. You don’t over-hire based on a guess.

Traditional factories do make wrong guesses about the future and overhire all the time. Example: https://www.google.com/search?q=Ford+f150+lightning+laid+off...

The whole article rests on this false economic claim, that traditional industries don’t overhire based on expectations. They absolutely do, ALL THE TIME. Manufacturing, automotive, airlines, energy etc. all of them make demand bets and lay people off when those bets fail.

Cheap money amplified this cycle, but this isn’t a tech specific "failure", it’s just how forecasting under uncertainty work.

It’s incredible how some engineers assume they understand economics, then proceed to fail on some of its most basic premises. This tends to happen when engineering-style certainty is applied to systems that are driven by incentives and uncertainty.

I will avoid getting into a “who understands economics better” debate.

But factory workers usually require specialized machinery, tooling, and physical capacity, which makes overhiring slower, harder and more constrained. Those investments force more deliberate planning.

By contrast, engineers mostly require a laptop and company hoodie... That low marginal cost makes it far easier to hire aggressively on expectations and unwind just as aggressively when those expectations change.

Factory overhiring can happen easily by adding speculative 2nd and 3rd shifts. No need for extra equipment, tooling, or physical capacity.

Lines with specialty equipment and tooling can also often be sped up. That can allow for other jobs to be added to all the functions that support the processes involved before and after the specialty equipment.

New employees also often require training and some apprenticeship time, meaning they can get hired ahead of actual demand.

I am really not debating whether over hiring is possible in factories.

in tech cost of hiring is lower which makes headcount a much easier speculative bet and layoffs a much easier reset when the bet fails.

The 90th percentile of factory workers makes $45,000. The 90th percentile of software engineers makes $230,000. Hiring in tech is insanely expensive; I'm not familiar with hiring in factories, but it can't possibly have the supply problems that tech workers have. I do on average 115 interviews for every person I hire in tech.

That $45,000 factory worker is often operating a $1.5 million piece of equipment with $10-50,000/hr of materials going through it.

It's an entirely different cost structure.

There exists greater issues in hiring for manufacturing when it is for new shifts. Master level technicians and foremen willing to work those hours can be exceptionally difficult to find, and everything flows out of these people. While similar issues likely exist relating to discovering talent for software development, I speculate that the factory will, in practice, have a harder time finding people (for new shifts).

My experience with seeing new shifts added is initially with only specific processes, and even with those it is with journeyman level technicians running a small crew to support relieving a bottleneck in production.

Alternatively, manufacturers can outsource until they have enough volume to add a shift, but across the economy the net is just transferring production from one facility to another.

> By contrast, engineers mostly require a laptop and company hoodie.

Alas, gone are the days when engineers too required specialized equipment like a desktop computer on the desk that you couldn't move with you. Every evening, you left it at office and went home to live a 100% home life. Alas, gone are those days.

I was a contractor for a FAANG. My immediate cubicle neighbor liked to work out on lunch break, and to hang his sweaty, smelly gym things on the framework of his desk to air dry when he returned. I would've KILLED for a laptop I could take to the complimentary office café so I could get something done without holding my nose. If I were a full employee, I could just ask for one. Alas, as a mere contractor I was something less than a person, so I had to remain tethered to my desktop per company policy.

I mean, if killing was an option, getting rid of the cubicle neighbor would have solved the problem as well.

Maybe for some. I've worked from home for 15 years and a huge thing that I've learned is that I have to have a hard physical boundary. My work laptop stays at my desk unless I'm on call and actively fighting a fire. When I want to use my desk for non-work things the work laptop gets put away.

Crunch time in those days sucked. I remember mandatory nights and weekends and the managers ordering in pizza for everyone.

> But factory workers usually require specialized machinery, tooling, and physical capacity, which makes overhiring slower, harder and more constrained. Those investments force more deliberate planning.

> By contrast, engineers mostly require a laptop and company hoodie... That low marginal cost makes it far easier to hire aggressively on expectations and unwind just as aggressively when those expectations change.

Software engineers also need

- specialized machinery (at least when they have to upload to some computation cluster or cloud), think for example of the costs for GPU/TPU clusters for AIs at the moment

- tooling: depending on the sector, the license costs for the sector-specific business software can be similar as expensive as specialized machinery

- mental capacity (instead of physical capacity)

> By contrast, engineers mostly require a laptop and company hoodie...

> That low marginal cost

Not true. That's how everything falls apart. Scaling software teams isn't simple. There's lots to account for. Do you just assume everyone commit to the same file and let it crash?

The more people, the more work is required to standardize, organize, document and fix gaps. You can say you're already at scale and things "should" be done but they never are. You hire a team into a specific area to find it was a giant hack supported by a part-timer and as you try to fix it the problems keep escalating.

What's the cost of a programmer-quality laptop, with two large monitors, plus licenses for all the software that they need? That's 2-3K.

Does anyone know what the typical tool cost is for a factory worker?

(And the tool cost for a factory worker can be zero if you're hiring for a second shift - they would use the same tools as the first shift, just at different times. In contrast, I don't think there are very many places that ask programmers to use the same laptop in shifts.)

>Does anyone know what the typical tool cost is for a factory worker?

It's probably lower. Apart from safety gear like helmets and gloves, everything else is most likely reused across shifts or shared across workers simultaneously (think industrial machines).

they even cut costs by leasing the computers...

I'd add that companies write off their equipment investment over a 3-5 year depreciation period. After that, when the laptops reach EOL, employees can often buy them through the company's EPP (employee purchase program) usually for just the fair market value, which might be a couple hundred € or sometimes even less.

So, eventually they recoup the equipment costs, wouldn't get surprised if they even make a profit out of it sometimes.

First thing they do, they write off VAT (20-23% of laptop price). Then at the EOL, they just set the EPP price to the higher market value. And return the cost.

VAT doesn't exist in the US (and sales tax, which we do have, is more like 5-10% of sale cost), so are you talking about something specific to tech companies in Germany or the UK or something?

Not that everything has to be about the US, but it's weird to make a claim about the tech market as a whole that doesn't apply to its biggest single region.

Yep, I've used the € sign for a reason, to make sure people won't get confused.

The article goes into considerable detail about the EU tech industry. My comment relates to that context.

I also want to note, that EPP isn't the correct term here. For US, EPP would mean Manufacturer Employee Purchase Programs for New Products with a discount. Like, if you work for HP, you can purchase a product it manufactures at a discount price for your personal use.

The EU practice that I was mentioning is called IT Asset Disposition through employer to employee disposal program[0]. I don't believe big companies in the US get involved in employer to employee ITAD for lots of reasons. But in EU, it's a thing, much to my surprise.

[0]: https://www.mddp.pl/disposal-of-used-equipment-by-an-employe...

>Yep, I've used the € sign for a reason, to make sure people won't get confused.

>The article goes into considerable detail about the EU tech industry. My comment relates to that context.

You know what, that's entirely fair. And I'll also note that American companies can claim depreciation to offset corporate income taxes, so there's some parity there, it's just s different mechanism.

Is that common? I've never worked at a corporation that had an EPP for EoL computer equipment. It always all went to a specialist recycling/refurbishing business.

I don't know about "common", but at one place, when they were retiring my machine, I asked if I could buy it, and they agreed. (Of course, for that to work, you have to be there long enough that they replace your machine...)

Throughout my career I’ve run into this approach a couple of times. All in all, it’s a fairly unusual practice—I was surprised myself.

The low marginal cost also means that the job market is easier for software engineers in times when expectations are optimistic.

This, and I would also assume it's easier to spot idle factory employees, where idle devs (especially remote ones) can be easier to miss.

And, (assumption again) the factory boss doesn't have an incentive to increase idle worker numbers, where a dev manager often benefits from being in charge of a larger number of hardly working people.

It is a lot easier for a software engineer to overcomplicate things.

All of a sudden it is no longer enough with a few shell scripts. No, we need a full kubernetes cluster to run a service used by 10 secretaries.

No, we can't just use PostgreSQL as a queue, we definitely need Apache Kafka for 1 msg per second.

This only holds for companies that do not have to comply with some regulation or standard, e.g. ISO 27001, to do business. Especially infrastructure, banking, and defense tech have high compliance requirements that also, and sometimes esp. cover software development.

Tech companies also benefit from over hiring. It gives them slack to absorb crises, and Fast Fuel to move quickly on new growth. Eliminating the fear of layoffs allows employees to take more risks and explore.

The current crop of tech companies cutting staff is going to lead to a large number of dead giants. The staff who services the layoffs will be risk averse, and defensible in a job cut situation. You see this in legacy firms where it takes 10 people to make a change because each person has a small slice of permissions required to effect the change. This pattern is by design as laying of any of the ten people on different teams would kill dozens of critical business processes.

This is not how you make high growth firms.

> It’s incredible how some engineers assume they understand economics, then proceed to fail on some of its most basic premises. This tends to happen when engineering-style certainty is applied to systems that are driven by incentives and uncertainty.

Software engineers are stupid, often because they think they are very smart (which breeds arrogance). And on top of that, they often have many biases that they often fail to account for (e.g. a preference for neat-and tidy-systems, leading them to get seduced by oversimple neat-and-tidy explanations, e.g. Econ 101).

There's also this tech exceptionalism/grass-is-greener bias where software engineers especially tend to romanticize other industries and professions.

My take is that the traditional industries you mentioned (manufacturing, automotive, etc.) are making expectations on the market for what it is they're selling. With tech though, it makes expectations on markets that are brand new, or don't exist, and/or have no proven track record whatsoever.

And with that, VR would like to take the microphone and have a few words…

The title could be re-stated:

The economy is screwed, tech is just the scapegoat.

People who already had plenty absorbed the cheap money, until there was basically not enough value left to go around for consumers to be able to carry on the way that was expected.

>this isn’t a tech specific "failure",

Nope, looks like every "market" has become more nonideal, and the more "financialized" they are could be what's making certain markets worse.

Not every job is actually on a "market", some are deep in and others not so much.

In the old days people held on to their jobs for so much longer that it's a really big difference when the actual "job market" in so many areas was virtually insignificant compared to 21st century rambling as the norm.

Regardless of pay, the more your job is part of a market, the more you would be subject to market forces beyond your control.

Markets are "always" irrational except for those times when they are neither in your favor nor against you. If a neutral situation holds for a period of time, that can be negotiated with a more "straightforward" approach than when volatility is the dominating factor. People might think with almost "engineering-style certainty". Once there are wild swings, it can be like a sine wave where half the curve is positive and the lower halves are negative. It still balances out to neutral but you may not know where you are at any one time. Every positive excursion will not last very long and be followed sooner rather than later by a negative equivalent in some way.

With a significant cycle occurring, then the only truly rational, neutral times are those brief zero-crossing events when the market reverses from favorable to unfavorable or back again.

If your only real opportunities occur when the market is in your favor, then you are dependent on the market being irrational which you need, but is about as uncertain as it gets. Opportunities like this can reverse more easily than the mainstream where they more often merely fade.

> It’s incredible how some engineers assume they understand economics

I would say most engineers. The reason is simple - basic economics is not taught in the public schools, and economics/business is not a required course for an engineering degree.

One of the best classes I ever took was a summer class in accounting.

Dunning Kruger effect, am I right?

We consider we are smart because we can make computers go beep boop so we know about the economy too. I mean, I am part of this too even though I (or we all) know the effect but I guess my point is that there should be an humility if we are wrong.

I can be wrong, I usually am. If someone corrects me, I would try to hopefully learn from that. But let's see how the author of this post responds to the GP's (valid, from what I can tell) critique.

Edit: Looks like they have already responded (before I wrote it but I forgot to see their comment where they said that its not at the scale or frequency we see in tech)

The scary part is when people who can make beep boop, and because the market has rewarded them for it, think they can skip the entire corpus of the humanities yet put forth opinions on how to shape society.

> We consider we are smart because we can make computers go beep boop so we know about the economy too

Funny, the person you are agreeing with made the strongest "I know more than you" flex than anyone.

They typically have an elastic workforce padded with several contractors or temp workers that can expand or contract based on market conditions.

It's incredible how engineers of all stripes assume they know all sorts of things they don't actually understand

That's a property of human beings in general. It's also a nice example of how sometimes a conundrum goes away when you make it more general.

That is, it seems incredible (going back to the GP) that engineers assume they understand economics when they don't. It's somewhat less incredible (applying your formulation) that engineers assume they understand things they don't. While it may still be incredible that engineers are so assumey, at least we no longer need to marvel at their assuminess about economics.

If we go one more step and state it as everyone assuming they understand things they don't, it's no longer incredible at all. What would be incredible is if anyone didn't.

> Cheap money amplified this cycle,

This is more-or-less the rub.

Fortunately we had a kinda-sorta sane monetary policy under the Biden administration once the pandemic started to ebb, but now we've got Mr. Appearances trying to push Jerry Powell to make stupid mistakes.

Sure, factories also overhire sometimes or shrink their businesses but not at the scale or frequency we see in tech.

I've never worked in tech, but I've worked at manufacturers of various different sizes and places in the manufacturing supply chain, including finished goods.

Manufacturers can't hire beyond the places in production that someone can stand and do something. There needs to be some kind of equipment or process for worker to contribute in some meaningful way, even if it is merely for a projection of increased production (e.g., hiring a second shift for a facility currently running one shift).

What I wonder is if in tech, the "equipment" is a computer that supports everything a developer needs. From there, new things can be added to the existing product.

Manufacturing equipment is generally substantially more expensive than a computer and supporting software, though not always. Might this contribute to the differences, especially for manufacturing that normally runs 24-hour shifts?

Manufacturing sector has the most job cuts over time because the prediction of China not surpassing them was wrong. Tech employment on the other hand almost never decreased.

While the surpassing is true, something I've found interesting is that across very different industries that have nothing to do with one another, and including publicly traded and private (though still huge) companies, I have heard directly from buyers that top management has given them a directive to find new suppliers in China.

From a supply chain management perspective, this does not make sense. The directive should be something like "find the best suppliers on the planet."

Only because their margins usually mean that those who do go out of business much sooner.

that's true but does tech generally hold a more aggressive default-growth stance?

From around 2010-2020 the stock market was rewarding growth more than profit. That means large tech employers hired like crazy to indicate growth.

Then came COVID and the economy contracted. As a result the stock market changed to reward profitability. So, excess developers had to go. We are still feeling this.

I do agree that AI is not to blame for this. In fact I will go further and claim that AI is a net negative that make this worse for the employer by ultimately requiring more people who average lower confidence and lower capabilities than without, but I say that with a huge caveat.

The deeper problem is not market effect or panaceas like AI. The deeper problem is poorly qualified workers and hard to identify talent. It’s easy to over hire, and then fire, when everyone generally sucks and doesn’t matter. If the average employed developer is excellent at what they deliver these people would be easy to identify and tough to fire like engineers, doctors, and lawyers. If the typical developer is excellent at what they do AI would be a complete net negative.

AI and these market shifts thus hide a lower level problem nobody wants to solve: qualification.

Qualification is a very difficult problem, but I think everyone resents the characterization of "bad devs". Things like the Metaverse failure - apparently $70bn spent for no results - are primarily management failures. Like the Cybertruck, they succeeded 100% at building a product that the CEO wanted. The problem is that the CEO is basically the only person that wants that product.

There's also the thought nobody wants to examine: what if the consumer market total spend is kind of tapped out?

Not only this. The marketplace got way less efficient. These companies are so large that they rival small states, with very little actual competition and command economies internally.

When management decides to build the metaverse, it should be a career-ending and company-ending move. What did the shareholders say? Nothing, they know that there's no competition. The leadership stayed. $70B!

Huge swathes of tech (and the economy at large) are like this. The stock market plays a huge part -- there are very few active participants, and individual pockets are bigger than ever (think e.g. Softbank); capital flows to whoever is largest. Even VC's talk about "what's your moat" -- they don't want you to out innovate, that's actually difficult; why do that, when you can find a regulatory loophole, or market power, and exploit that instead.

When one earns better return on his dollar from monopolization and market power, it's a very very bad sign for the economy at large. And we very clearly have not yet learned this lesson, even when signs of it (China out innovating us in a rapidly growing number of industries; political instability; state capture, etc). We are already a couple decades into this habit and it will not end well for us. I think this is an issue with USA industrial strategy at large. We say over and over again, we need to do the hard stuff, we need to invest in energy, batteries, 'hard tech' etc. But what did we do? $1T to Sam Altman sitting on stage in the Steve Jobs outfit, doing the App Store for ChatGPT.

Individual SWEs are doing what individual people did in the Soviet Union. Join the party, read the party book, and get a cushy mid-level bureaucrat position. It beats working the factory, that's for sure!

Yes and no. Excellent developers deliver excellent products, like with the Cybertruck example. I wouldn't buy one either, but it appears to be well crafted.

Stellar developers are one step better. Yes, they too delivery excellent products, but they also produce things of value that nobody asked for. Business examples include Teflon, Postit Notes, antibiotics, linux, git, and much more.

The US Army changed leadership methodologies about 20 years ago to account for this. The current leadership philosophy is called Mission Command. In the fewest possible words a leader provides a stated intent and then steps back to monitor while subordinate leaders exercise their own creative initiative to meet that intent. The philosophy before that was called Military Decision Making Process (MDMP). MDMP required leadership buy in for each step of a process from among a set of discussed courses of action. MDMP is now largely relegated to small personnel teams.

Teflon and Antibiotics were scientific discoveries just through a pursuit of curiosity and applying the scientific method. Not sure these scientists who discovered them fit in your developer example… totally different contexts.

They were both discovered by accident on items bound for the trash, provided we ignore Ernest Duchesne.

i think the cybertruck is pretty well known to be crafted poorly, doesnt it always have problems with pieces falling off, or bursting into flames?

its insane that there wasnt any consequence for the metaverse at all. Oh yeah, we built a second life clone based totally around the idea that people want to spend rent money on fake digital real estate. Of course it tanked, no one was brave enough to point out ahead of time how bad an idea it was? And this doesnt hurt their standing, stock price, or marketability at all?

What makes you say it hasn't affected their stock price? Seems likely the Meta stock would be much higher if they had an additional $15B profit on their books each year.

Plenty of people wanted the Cybertruck, it's just that price is too high. It was originally announced to be under $40k, and with incentives, could have been in the $30k's.

The F-150 Lightening had the same problem.

It wasn't covid - it was the post-covid coming down from all the free stimulous and ZIRP. The Russian war in the Ukraine is a much closer market to when the economy started tanking for devs.

covid was a last gasp for zirp. the interest rates were growing since 2016 and would've remained high if not for the pandemic. covid required a quick return to zirp to save the economy from a crash, then required a quick return to high interest to save the economy from inflation.

if not for covid, the zirp era would end more gently. covid overhiring was the last hurrah for companies to use the low interest. if not covid, there wouldn't be overhiring and subsequent firing

the market would be as bad as now (or dare i say, *normal*), but it would be stable bad, not whiplash.

How exactly are good doctors easy to identify and hard to fire? And how does it follow that AI is a net negative when wielded by professionals who are excellent at what they do?

If people can't identify qualified professionals without relying on credentials, they probably aren't qualified to be hiring managers.

There are a couple of things that identify talent in the qualified space:

* Peer reviews in the industry

* Publications in peer reviewed journals

* Owner/partner of a firm of licensed professionals

* Quantity of surgeries, clients, products, and so forth

* Transparency around lawsuits, license violations, ethics violations, and so forth

* Multiple licenses. Not one, but multiple stacked on top of a base qualification license. For example an environmental lawyer will clearly have a law license, but will also have various environmental or chemistry certifications as well. Another example is that a cardiologist is not the same as a nurse practitioner or general physician.

Compare all of that against what the typical developer has:

* I have been employed for a long time

More elite developers might have these:

* Author of a published book

* Open source software author of application downloaded more than a million times

Those elite items aren't taken very seriously for employment consideration despite their effort and weight compared to what their peers offer.

They are not taken into account simply because they may be meaningless to job advertised.

For example no company I ever worked for (maybe 7 over 20 years) needed publishing academics. Is the fact that you published a book about some DB architecture 10 years ago going to make you a better team member and deliver things faster? Maybe, or maybe not, how could hiring folks know? You measure and judge what you can, ignore the rest since it can be + or - and you have no clue, not even about probability spread.

Doctors with many licenses may be better, or maybe they like studying more than actually working with patients and thus be possibly even worse than average, how do you want to measure that? A stellar doctor may simply have no time to do anything beyond her/his current work due to also dedicating time to their family and raising children. Quality of a doctor, especially surgeons is mostly function of work already performed (knowing closely tens of doctors from all branches they themselves often claim this), not some extra papers. And so on and on.

Yes, most employers in tech are not looking for published academics. That’s a bit of an oversimplification.

The actual problem is that developers are made into a commodity because they are an unvalued cost center. Developers do not make money. They only take money. So, the goal is to not train them and replace them as conveniently as possible.

The result is to not look for talent but instead equate the requirements to a lowest common denominator. That minimizes personnel management friction at cost to everything else. We all know this. The real concern for developers is why that is allowed to occur in software but not other professions.

> And how does it follow that AI is a net negative when wielded by professionals who are excellent at what they do?

Simple, the 80% of code monkeys who are not good at what they do will cause way more damages than the "professionals who are excellent at what they do". And out fo tech I can guarantee you the vast majority of people use llms to do less, not to do more or do better

It's also easily verifiable, supposedly AI makes everyone a 10x developer/worker, it's been ~3 years now, where are the benefits ? Which company/industry made 10x progress or 10x revenue or cut 90% of their workforce ?

How many man hours are lost on AI slop PRs? AI written tickets which seem to make sense at first but fall apart once you dig deep? AI reports from mckinsey&co which use fake sources?

The big wins I've seen with llm tools is in translation more than the actual code.

We have been able to move our "low cost" work out of India to eastern Europe, Vietnam and the Philippines; pay per worker more, but we need half as many (and can actually train them).

Although our business process was already tolerant of low cost regions producing a large amount of crap; seperate teams doing testing and documentation...

It's been more of a mixed bag in the "high skill" regions, we have been getting more pushback against training, people wanting to be on senior+ teams only, due to the llm code produced by juniors. This is completely new, as it's coming from people who used to see mentoring and teaching as a solid positive in their job.

It's really only in the last year the LLM's have gotten great and can output massive blocks of code that are functional.

LLM's are at least a 10x speed up on the 'producing code' portion of the job, but that's often only a fraction of the overall job. There's lots of time spent planning and in meetings, doing research, corporate red tape, etc.

For writing code and unit tests, generating deployment yaml and terraform, for me it's easily a 30x speed up. I can do in 1 or 2 hours what would have previously taken a week.

Even if the average employee is pretty good at what they do, why wouldn't AI boost that productivity to another level?

I think we'll see something counterintuitive happen where hiring picks up dramatically. Companies are willing to overspend and over-hire to automate everything away once and for all.

> If the typical developer is excellent at what they do AI would be a complete net negative.

No. There is work done by AI today no developer can match in speed and speed is relevant for development cost. Excellent developers would very likely employ these tools.

Anecdotally, I didn't see more safety for engineers working on cash cows. Quite the contrary, if a product is already bringing revenue, it is an easy decision for the business to squeeze a bit more margin by letting people go. Stable, cash-generating projects are often first to be put into efficiency/maintenance mode.

Also anecdotally, I've had a handful of software development positions throughout the years (never at a position with more than 200-300 person company) and have yet to be laid off due to money. I've yet to be laid off at all, but that's irrelevant.

I truly believe that these new tools will actually hurt the bigger companies and conversely help smaller ones. I'm in healthcare. The big players in the EMR space are Epic and Cerner. They are one-size-fits-all behemoths that hospitals have to work against than with. What if, instead of having to reach out to the big players, the economics of having a software developer or 2 on staff make it such that you could build custom-tailored, bespoke software to work "with" your company and not against?

> What if, instead of having to reach out to the big players, the economics of having a software developer or 2 on staff make it such that you could build custom-tailored, bespoke software to work "with" your company and not against?

The behemoths exist especially, but not exclusively, in that space because regulations (correctly) are steep. In the case of hospital systems you're talking both the management and protection of both employee and patient data. That's not to say of course that the behemoth's are particularly good at that, it's merely that if the hospital rolls it's own solution, as you suggest, they then take on the liability should that system go wrong. On the other side, if Epic has a data breach, every hospital shrugs it's shoulders. It isn't their problem. And, even more fundamentally, if Epic as a product sucks ass... well. The employees didn't choose it, neither did the patients, leadership did.

You see these relationships (or lack thereof) all over the place in our modern world, where the people doing the work with these absurdly terrible tools are not given any decision-making power with regard to which tools to use. Hell, at my workplace, we actually have some in that leadership asks if we're happy with our various HR softwares and things, but fundamentally, they all pretty much suck and we're currently sitting at the least shitty one we could find, which is far from a solid fit for our smaller company. But it's the best we can do because none of these suites are designed to be good for people to use, they're designed to check a set of legal and feature checkboxes for the companies they sell to.

Honestly I don't know how you fix this, short of barring B2B SAAS as an entire industry. Time was, when you wanted to run a sales company, you had to run your own solution to keeping track of internal data. Salesforce didn't exist. You had rows upon rows of file cabinets, if there was a fire data was a lost, if a disgruntled worker stole your sales list and sold it to a competitor, that was it's own issue to deal with. Now crooks can crack the locks off of NetSuite and steal your whole fucking business without even knowing where the hell your HQ even is or caring for that matter, and our business universe if you will is bifurcated all to hell as a result. Companies are engaged in constant games of "pin the legal responsibility on someone else" because to compete, they need internet and software based sales and data management systems, but building those systems is a pain in the ass, and then you're responsible if they go wrong.

Aren't they still going to need to reach out to the big players because of the regulatory environment? And for good reason, as it happens. We don't need hospitals handing over the public's health data to the cheapest person they can find to prompt it all into Claude.

You can be a small player and still deliver immense value in health care I work at a firm in a niche with about 30 employees. We follow all regulations and go above and beyond them in regards to security.

Absolutely. I'm in the same boat (a bit bigger with around 200).

It's crazy the underlying business has succeeded despite being boxed in by the software they're currently using. And at least in my niche, you only have a few options. Each with their own unique quirks.

Instead, EMR's could position themselves as more of a "data provider" where you build bespoke software on top of the underlying storage. And to that end, having the abiliy to pump out small, focused apps can be really beneficial.

Just anecdotally, my experience was the total opposite. I didn't work in the health care industry long though and I think you're probably right in general. But you might also find there's a lot of variation between small companies too and a lot of failures for every success I suppose.

> Aren't they still going to need to reach out to the big players because of the regulatory environment?

First, saying "We can now build software faster" doesn't imply that "we" won't eventually include professionals. There is nothing stopping someone from building up an app and having people come in to polish it up.

Second, "regulatory environment" doesn't actually mean somethin because every part of the industry has different regulations and requirements. There are different standards for what big hospitals can use and the software requirements than there are for home care software. So trying to wave this "you can't because of regulations" wand doesn't make sense if you're actually in the business.

Third, I was speaking more to the small-medium sized agency.

Fourth,

> We don't need hospitals handing over the public's health data to the cheapest person they can find to prompt it all into Claude.

Means absolutely nothing since you don't need to feed health data into a Claude instance to build healthcare apps. It sounds like you aren't in the field or familiar with it.

And lastly, if you're a Microsoft customer with a BAA, then you're already covered by HIPAA. Again, not something you would know if you weren't in the industry, but now you do.

What if, instead of having to reach out to the big players, the economics of having a software developer or 2 on staff make it such that you could build custom-tailored, bespoke software to work "with" your company and not against?

Because the hospitals those practices want to associate with say "we're on Epic and expect you to be as well"?

Wife in healthcare management...overhear this conversation once or twice a week.

Also the nurses in the floor learn the system and many are not great at adapting to different interfaces. Travel nurses who come in and only worked with GE or Cerner and now having to use Epic causes all kinds of issues.

Also from what I’ve seen is big city hospitals use a mix of all three. Which I believe actually creates an opening as it shows a willingness to use different walled gardens.

However I think there are a lot of opportunities to just build on top of these systems rather than wholesale replace. Because they’re one size fits all and the people who work on them haven’t a single designer bone in their body the interfaces are terribly clunky and slow. Macros exist but seemingly no one is aware of them. It’s rife to build better interfaces tied into macros behind the scenes.

Spot on. And "build on top" is what I'm working on. Tilting at deeply entrenched windmills is a generally a fools errand (as Cervantes said).

It's probably risk and liability and not development costs that keep things from moving in house. Not things AI is great at mitigating.

That's not actually true. It might be for the bigger companies, but certainly not the smaller ones.

And "risk" in this industry could mean any number of different things. We, as a medium-sized provider, have a BAA with Microsoft for HIPAA. That means that I can utilize information I've gotten from my EMR and build line-of-business apps that bridge the gaps between other systems they may have to work in. In fact, our Microsoft tenant has a much higher level of security than the underlying EMR.

I'm quite literally living what I spoke about above. The reason why I was brought in was because teh current CEO has a very tech-focused mindset, otherwise agencies usually can't afford a full-time software developer. Now, those economics are changing.

Also, I haven't heard of an agency that didn't want custom reports built because they found the default ones unsuitable. So even something like the ability to mainline Power BI reports would be compelling.

Hospitals are huge liability sinks. Doctors are constantly sued for killing, injuring, or traumatizing patients, because it's impossible to consistently save everyone.

Which is why they don't food liability when they can. Is it worth saving $100,000 a year if it allows the lawyer to say "if they had used industry standard software would the medical error have happened?"

The research hospital in my neighborhood has a whole biomedical engineering dept and regularly tries out new medical technology on me.

They consistently try non-standard approaches if they feel like it can improve the standard of care since their commercialization team can make more money. They can also iterate faster and deliver better outcomes.

I'm guessing either EHR software is uncompetitive or nobody has tried it yet. Or it's just because I live in Toronto and we have a really good healthcare system.

Trying to improve medicine has a different upside and different calculation than making software less annoying.

Improved EHRs would improve medicine by making doctors more productive. Increases the amount of time they can spend billing instead of on administrative overhead. More billing is more money.

I don't think this is bureaucratic maliciousness to kill innovative EHRs. My guess is it's a really hard and boring problem to solve due to the integration work which makes it hard to break the network effects.

It may be not such a bad idea because many engineers have an itch for fixing things that aren't broken.

It is rather that many software developers see how bad the code is, and thus attempt to reduce the code debt if possible. I have rarely seen software developers fixing things that aren't broken (though it is often not easy for managers and people who are not deeply knowledgeable about the project to see why what is there is broken).

On the other hand, I have seen politically very adapt software developers who actually rather want to managers to advertise some technology that they would love to introduce in the projects.

Yeah, 'cause slide rules were doing the job just fine!

> Stable, cash-generating projects are often first to be put into efficiency/maintenance mode

Or they're actively enshittified, aiming to extract more short-term revenue at the cost of a long-term future...

If you're a company where the future looks uncertain, short term over long term starts to look mighty appealing

Interesting framing. The article makes a compelling case that we're seeing the hangover from 14 years of ZIRP-fueled hiring rather than an AI apocalypse.

But I'm curious what people think the equilibrium looks like. If the "two-tier system" (core revenue teams + disposable experimental teams) becomes the norm, what does that mean for the future of SWE as a career?

A few scenarios I keep turning over:

  1. Bifurcation - A small elite of "10x engineers" command premium comp while the majority compete for increasingly commoditized roles                                                       
  2. Craftsmanship revival - Companies learn that the "disposable workforce" model ships garbage, and there's renewed appreciation for experienced engineers who stick around                 
  3. Consulting/contractor becomes default - Full-time employment becomes rare; most devs work project-to-project like other creative industries

The article argues AI isn't the cause, but it seems like it could accelerate whatever trend is already in motion. If companies are already treating engineers as interchangeable inventory, AI tooling gives them cover to reduce headcount further.

For those of you 10+ years into your careers: are you optimistic about staying in IC roles long-term, or does management/entrepreneurship feel like the only sustainable path?

As someone with many animator friends, this sounds very bleak. Their work processes are very similar to software engineering, with the difference that their hiring process is much quicker (they just show a bunch of reels and shots they made for previous films or cartoons, and they’re hired). The sad part is that they have almost no labor rights, and competition is incredibly high, which means pay is very low and turnover is high. All these years, I’ve been setting my expectations that one day my field may become like that.

The difference is animation is part of the entertainment industry and software engineering is part of every industry. I don't really think it will ever be like animators are today, but I wouldn't be surprised if wages fall.

Well I think there's an oversupply of CS engineers, not of animators

There's definitely an oversupply of animators, but probably not to the extent of CS at the moment.

#1 is inevitable; the Pareto distribution is everywhere. I read a paper on how it naturally shows up when people can act on preferences, but can't remember the paper (and it was in the context of why cities show a Pareto distribution)

#2 there will always be craftsmanship companies, but they will always be small companies, or a small team within a big organization. Craftsmanship doesn't scale; engineering does.

#3 contracting won't become the default. Many places have experimental or well-contained projects, or not enough ongoing work for full-time, but anywhere that custom-built software is important to the business will always need changes and maintenance. The problem with using contractors is that after their contract is over, they go find another contract, so they may not be available when you would like to re-use them, and then you've got to start over with a new one.

Look at any other industry. It's going to be like that.

Low–wage employees without agency.

"Consulting/contractor becomes default - Full-time employment becomes rare; most devs work project-to-project like other creative industries"

I'm in the tech industry and have been doing this for 12+ years now. In the beginning, it was because I wanted to live overseas for a few years, without a break in my career.

Now, it's about survival. I buy my own health insurance (me and my family) in the marketplace every year (so I'm not tied to an employer), work with multiple clients (I never really have to worry about getting laid off), and make much more than a FTE.

While all my friends in tech are getting laid off or constantly in fear of getting laid off, I don't have to worry.

I also find that because I touch so many different technologies, I have to turn down work. I turned down a company last year, that wanted me in-house and one this year that would have been too demanding on my schedule.

It's also flexible and always remote.

I was consulting like this too, but my wife also had a full time corporate job. It all kind of ended with her team having layoffs around the same time that most of my clients figured out that they could use AI to do most of my work at a tiny fraction of my rate. I had built up a lot of experience working with oil and gas software, and I thought that was pretty solid, but it's hard to compete with $20 a month. Anyway, after all that, I found a stable job with good health insurance.

Have been doing this for ~3 years as a way to bring into the industry. Has more or less worked (to that end), but the art of finding + maintaining a pipeline of potential clients while working contracts full-time to sustain a family is.. difficult. (And now that I'm qualified to get a real job in the industry, many raise eyebrows at the plethora of short-term contracts).

I'm happy to hear it's been working out for you, though. How do you manage/succeed?

Are you a one-person shop? How do you find clients?

Almost always they start by having connections that hire them (old colleagues, former friends, etc.), building out those connections (conference talks, doing really good work, writing high quality blogs), and then if you're lucky, some word of mouth.

Good points - admittedly, I didn’t put enough effort into building connections through different pipelines back when I was contracting. Upwork and a few personal connections were my sole sources.

It just felt really difficult to do both the engineering work while trying to do customer development at the same time.

The fact that OP has been able to do this for so long, while supporting a family, piqued my interest.

Can confirm.

How did you get into this? How would you recommend transitioning from FTE to this life?

I am 10+ years into my career. I don’t think mgmt / entrepreneurship feels like the only sustainable path. But I believe I may become a manager of a 5-10 Claudes.

What are your Claudes going to be building and who is going to fund it?

I always saw it as bimodal (even before LLMs) - you have folks working in regular shops making average comp, and you have the big tech elites earning high base + equity comp.

The Pragmatic Engineer argues it's actually trimodal (at least in Europe): https://blog.pragmaticengineer.com/software-engineering-sala...

A thought I had about this topic, this is a simplification of reality to illustrate a point:

Software developers are doing R&D, you create new stuff that continues to exist forever. This is unlike most jobs, in which you produce goods and services that are consumed and then you have to produce them again.

What if we are getting to the point where all of the low-hanging stuff is invented? For example, every bank has an app which works and rarely needs to be changed. Or take a social network like Facebook, going from zero to a product with 1B users took a lot of development but since then, it's been mostly static, why employ thousands of developers dedicated to Facebook? Etc.

These are the right questions and core to the actual “ai race”

Before ai, all we had was compilers and interpreters to take instructions and turn them into machine code and byte code

A lot of political painstaking went into which compilers and even with “better options” there’s only really a couple big fish of workflows to take an orgs ideas to production.

What passes as a compiler and what passes for a programming language exploded.

I’m very interested in “the final compile target” of these systems AND the output of that still being human readable and influenceable.

The ridiculous thing is that we're spending trillions of dollars to develop these coding assistant AI things at the same time we're running out of useful stuff to code.

> it's been mostly static

In a well-functioning competitive market, no company should be able to rest on its laurels. The problem is industries have consolidated and trustbusters are nowhere to be found.

Notice when tech is new (the web, smart phones, AI) there's an initial burst of competitive companies? That's because the market hasn't consolidated yet. Ask yourself how many dot-com millionaires would realistically be able to duplicate their success in 2026, given the same product but launching today.

Aside from consolidation, discoverability is a huge problem, especially in the era of AI slop. Building a superior product is easy, getting it noticed and building traction is hard.

I'm not arguing against the core arguments of the article (I agree with most of the points), but on the other hand, software development is (at least currently) an essentially iterative process - one that differs greatly from other production processes (e.g. buildings, cars). We all know how difficult it is to estimate how much development time something takes. Planning is hard and outcomes have therefore greater variability.

I generally agree with you, but if you look deeper, cars, buildings, and the underlying know-how didn’t appear in a day either.

Those were also iterative processes: first tires and mud houses, then horse carriages and brick houses, and eventually cars and buildings.

In that sense, it’s not fundamentally different from engineering today. Working on core engineering functionality of a company is essentially the same kind of process.

The difference lies in whether you’re working on core functionality, or on some iterative experiment that nobody knows will succeed.

When it comes to cost rebuilding, we can't compare the software engineering with other industries(like cards or buildings). I think this makes it much more iterative compared to them. Living in North America, if feel like 99% of aparatments and houses can be grouped into 5-10 floor plans. I think thats because when you are designing a new building or house you really can't do much risk. You do what has already worked. Software also have trends, but they change so often. You also can't do A/B testing or targeting or measure every single interaction potential customer has with your product. The nature of building "Software" really brings so many options to the table which increases the number of iterations by order of magnitude.

I'm talking about how a single product is produced, not about its evolution through centuries. Anyway, the point wasn't to compare specific details, it's just an analogy.

The other major factor is that increasing dev work for "side bets" doesn't require large Capex investments which typically other industries do (building a new car as a moonshot project? you have to spin up a whole new factory). all you need is some office space and not even that if you're hiring remote

Your aren't building a car when you are writing software, you are building a car factory.

> Most engineers (including me) spent months grinding LeetCode at least twice in their career, studying system design, and passing grueling 6-round interviews to prove they are the “top 1%.”

Really grateful that the opportunities I've been given weren't predicated on knowing things completely irrelevant to my job. I have spent exactly zero time solving LeetCode problems in my career (beyond algorithm stuff in college).

It's perfectly possible to have a successful SWE career without touching Leetcode-style questions. It's just that most of those jobs don't pay well.

As a Clojure developer I have the opposite experience. The more they ignore my open source work, the more they never call up any of my references, the more they give me useless test jobs and assignments unrelated to the actual work, the more it's a signal of a place with poor engineering culture and generally also not that great salaries.

However the places that actually do read my open source work, do contact my references, and where the interview has had no tech assignments of any kind other than a simple discussion about a variety of topics, perhaps just going over some of my OSS projects, the higher the salary has been.

This is in Northern Europe though, your mileage may vary.

IMO, this is a not-wrong but less insightful perspective on what Ed Zitron talks about in The Rot Economy. Cycles of overhiring and layoffs happen, but they're not the core mechanism. AI isn't the cause, but it's also not a scapegoat. It's just the current placeholder, like blockchain and the metaverse, that allow companies to have their valuation based on growth rather than profit.

https://www.wheresyoured.at/the-rot-economy/

Right, AI isn't the reason, but it sure as hell is an accelerant and part of the pattern that ultimately is extremely unsustainable. It's going to be really ugly when it ends but it's inevitable.

Your linked article seems aligned with https://www.slatestarcodexabridged.com/Meditations-On-Moloch

This tracks, reminds me of Cory Doctorow's talk on reverse centaur situation where he gave a nice rundown of the tech market of the past 15+ years.

Do anything and everything to remain in "growth stock" category. Spend money on useless features, on engineers working on those useless features - as long as it will make your company look like it has bright future and space to grow.

Wasn’t familiar with this, tracked it down

https://locusmag.com/feature/commentary-cory-doctorow-revers...

> There’s a bit of automation theory jargon that I absolutely adore: “centaurs” and “reverse-centaurs.” A centaur is a human being who is assisted by a machine that does some onerous task (like transcribing 40 hours of podcasts). A reverse-centaur is a machine that is assisted by a human being, who is expected to work at the machine’s pace.

>In traditional industries like manufacturing you don’t hire 500 factory workers unless you have a production line that needs them. You don’t over-hire based on a guess.

This is interesting, in my experience its seemed to be the opposite.

In manufacturing, its must easier to come up with a specific number of employees you need for a given project or contract.

If the contract is expected to sign you may hire early to get ahead of it.

If the contract falls through, or an existing contract is cancelled, you know exactly how many people you need to cut to balance labor with your current commitments.

I don't really understand this writer's objection: Big tech is big money and big risks. If some giant FAANG company is going to take a gamble on paying you $350,000 TC you should be squirreling most of that away for yourself in case the bet goes south.

If you want stability, go write Java for an insurance company for $85,000/year in Hartford, CT.

OP is horrified to discover risky gambling happening in Las Vegas.

hey I am the writer of the post anecdotally, my last job was an insurance company I got laid off from there too :)

> Yesterday, the news of 16k Amazon layoffs plus two LinkedIn posts on the same topic back-to-back encouraged me to finally write about it.

Amazon is fundamentally a logistics + robotics company and is one of the worst companies to join for 'stability' as they have razor-thin margins.

With almost 1.6M workers, the layoffs there are at least in the 5 figures and they will not stop to do the easiest thing possible in order to increase profit margins and that is to take jobs away from warehouse workers (using robots) and corporate jobs (using AI agents).

> Most engineers (including me) spent months grinding LeetCode at least twice in their career, studying system design, and passing grueling 6-round interviews to prove they are the “top 1%.”

Leetcode can be easily gamed and cheated and is a waste of time.

Now you need to make money for yourself instead of dancing around performative interviews since an AI Agent + Human out performs over 90% of workers doing the mundane work at Amazon anyway.

You are being scammed without knowing it.

> Amazon is fundamentally a logistics + robotics company and is one of the worst companies to join for 'stability' as they have razor-thin margins.

You seem to forget that AWS exists.

They have an 11% operating margin. That is far from razor thin. Their biggest business is AWS. They have subscription income, and they sell digital downloads and streaming which are high margin.

https://s2.q4cdn.com/299287126/files/doc_financials/2025/ar/...

Yeah, nobody makes this “margins are too low” complaint about Costco, which makes the majority of its profit on memberships, the exact same business model as Amazon Prime.

Amazon the logistics company is paid for by the $100+ per year that its customers just give to Amazon to get basically nothing in return.

All thanks to previous layoffs since 2022 which they cut 27,000 jobs in 2022 to 2023 due to mass over-hiring.

Compared to the other FAANG companies, these margins not only thin, but terrible and Amazon has the worst margins out of FAANG regardless of AWS or not.

Ofcourse, AI does have an impact. We can't close our eyes to that. Atleast, it created a belief that massive layoffs are affordable now without affecting productivity.

Mind you that the IT over investment sucked money out of other industries. My friends who chose different career paths do not seem to be particularly content either.

It's insane how many billions went into idiotic "tech" companies like wework when it could've been invested somewhere with an actual outcome or benefit for society.

Let's not even bring the gig economy into discussion..

The main issue IMHO is the monopolization of the industry, especially in the US. Once the giants do layoffs, the rest of the market can't absorb the people effectively, which leads to oversaturated job market.

We can of course discuss how many people got into industry during COVID heyday and whether they should have, but mostly I think it's about those behemoths having disproportionately high impact on the entire labour market.

Having stable core revenue teams and disposable experimental teams seems like an excellent way to ensure the experienced developers will leave as soon as they can, and that any new knowledge leaves the company as soon as possible.

So in the end you lose both your ability to acquire new knowledge and to keep existing knowledge.

There has to be a better way surely?

Should information technology be a stable employment sector?

As far as I'm concerned, the main purpose of IT is to automate work. Tech companies make these systems of automation and provide them to other industries, so they can automate.

Making a program or an IT system is something you only do once. So once it is completed, it is expected that a lot of people who helped make it have to go. It's like building a skyscraper. Massive amounts of work to build it, and when it's finished, most workers have to move on.

Of course an IT company can continue to expand into perpetuity, but what if they don't have the leadership talent or resources to create a new giant project after one has been finished? Then the sensible thing is to down-size.

"Well don't hire too many people in the first place to rush your project into completion" - Then you get left behind.

There is churn in the work being done. An automation solution for one company shouldn't be expected to work for the next company. Every company has different processes, and developing software to fit the exact needs of one company will continue to be useful.

Some software is finished, like Microsoft Office 2003, and requires no additional work except to force ads on people. Those jobs may end.

Mostly true, but AI accelerated that process:

- Senior Engineers now often is sufficient for most tasks, Junior Engineers seems like a burden rather than a boost during development process

- Companies feel comfortable with hiring fast and firing fast

- Tech Market is now flooded with not-so-good engineers having good experience with good AI coding assistants - which already are capable of solving 80% of the problems - they are ready to work for much less than really experienced engineers

In general, yes, companies overhired many software developers, hoping they will continue hyper growing, but then reality has kicked in - this was not sustainable for most businesses.

The author describes hiring strategy relative to Fed policy as one assumption that presumably motivates the current context in the market, but completely fails to make a point about AI, or to generally back their claims. In fact, even the main claim seems to be pulled out of the hat wrt to Europe where there’s no Fed. No hiring/layoff numbers, etc. I get it that it’s just a guy with a blog, but it’s on top of HN now, and IMO vacuous, describing one motivation that’s been floating around for quite some time. Perhaps as long as they wanted to write about it until this “last straw”

Europe is still connected to US financial markets. The USD is the most influential currency. When it contracts, money in general contracts.

This is just scarcity based economics failing us in the ways that it has been for decades now. The only thing that stands out about tech is that from 2010 to 2020 it seemed to be withstanding the rot.

Since the world has finite goods and everyone wants more, I'm not sure what kind of economy besides "scarcity-based" you expect to find.

That worked well back when what we wanted more of were things that we all agreed upon were desirable. More food, more housing, more cars and tools and clothes.

Nowadays most of our efforts are in pursuit of contradictory goals. Creating an AI god, going to Mars, ethnic cleansing projects... these aren't things we unanimously want more of, they're one of two alternatives that some of us want to achieve and the others want to prevent. The logic of scarcity is a poor mediator for such things.

We don't have to dispense with scarcity entirely in order to stop using it as a proxy for decision making about outcomes that have nothing to do with scarcity.

I think there's an argument that AI is helping the (non-AI) software job market. If tech companies are seen as laying off "too fast", then investors will penalize them for not retaining enough people to compete in AI. So companies have to do some layoffs, both to rebalance for the economic downturn and to claim "progress in AI", but not so much that it makes them look weak to investors. Whether they actually need the employees for anything is secondary.

Could this not be simply summarized as ZIRP fueled a bubble in tech long before AI? Mass layoffs have been cycling on and off since ZIRP stopped. I doubt we will see that change anytime soon.

I don't really understand what the author is arguing for here. Yes, tech companies (and everyone else) hired a ton of people when money was cheap, and now they are doing lay offs. I suppose the alternative would be employing people for life? Or that it should be costlier to fire people (ie like in Europe)?

Also, if you are using AI to even write such a simple blog post, then perhaps corporations are indeed using it for all kinds of purposes too, and that undoubtedly reflects on their hiring.

The author never really argued for anything. He's just whining

Is this just for the big guys like FANG, AI companies?

There is huge part of tech market that is just humdrum blue color software. Keep the ERP system running, build a new efficiency report, trouble shoot why the payroll missed bob last week because of a un-validated text entry field.

Or because of the years of zero interest, tons more people went into software, so now it is over-populated, and thus puts pressure on regular hum-drum software jobs.

Proven businesses can always borrow at fairly low rates. When capital gets really cheap it starts to incentivize greater amounts of risk taking because investors actually want risk.

If you are starting a dry cleaning business, you have a cost of the equipment, rent and other well known factors. Starting a tech company in a new and unproven area has different expenses and a different risk/reward profile.

Malinvestment can come in a lot of flavors. Cheap capital will result in too many dry cleaners and also too many startups that probably shouldn't have gotten funding.

The downside comes in various forms. 1) existing dry cleaning businesses are less profitable because of increased competition, and 2) startups hire scarce engineers and drive up wages, which drive up costs for everyone.

Cheap capital is justified bc the goal is growth, but it is a blunt instrument that creates hot spots and neglected areas simultaneously. Compare the approach used in the US with the approach taken by China. Chinese firms face significantly more competition than firms in the capitalist US, but overall China's policies are crafted with a more deliberate eye toward their distributional consequences and notions of the greater good are much more subject to sharp critique and pressure across social and industrial strata.

What we are seeing in the US is that policymakers have come to believe that the growth-focused approach is an escape hatch that can be used to reduce the effects of other bad decisions, but at some point the size of the inflated economy gets big enough that it takes on a political life of its own -- post-911 defense contractors have dramatically more lobbying and policy-influencing power than they had prior. Today, systemically risky financial industry participants have significantly more political clout than they had before the 2008 correction.

In other words, the fabric of (political) reality shifts and it becomes hard to identify what normal would look like or feel like. In my view, AI adds fuel to the existing fire -- it rapidly shifts demand away from software engineers and onto strategists -- give the team a strategy and now with AI the team will have it done in a few weeks. If not, a competitor will do it without poaching anyone from your team.

And market forces include both creative and destructive forces. Firm failure is a feature, not a bug.

Cheap venture capital is uniquely driven by the interest rate more than any other factor. Low interest rates drive money away from safer vehicles towards more risky vehicles because they still offer a return. This is good far people starting companies, but in the long run the decision makers on those investments almost always turn out to have mis-priced the risk factor and end up with negative returns.

This then causes the market to dry up again and if the interest rate hasn't dropped even further then a lot of companies that need follow up investment will now get killed off. It's a very Darwinian landscape that results from this and I've been wondering for years if there isn't a better way to do this.

Excellent points. You've perfectly described the brutal, interest-rate-driven VC cycle -- capital floods in, risk gets mispriced, and the market eventually corrects with Darwinian force. That's the "blunt instrument" in action.

Meanwhile in China, the approach is fundamentally different. Capital isn't just cheap; it's strategically directed by the state with goals beyond financial return. The aim is "new quality productive forces" -- slow-burn, systemic growth that reinforces social stability and industrial upgrade, not a boom-bust race for unicorns.

The current AI boom is our real-time experiment to see if this is the "better way." The U.S. model, as you note, is driven by massive private investment (over $109B in 2024) and is prone to hype cycles. China's model is state-planned, focusing on the "AI Plus" integration of technology across its industrial base, despite investing less ($9.3B) and facing constraints like advanced semiconductor access.

We're watching two competing logics: one seeking market-defining breakthroughs through volatile, capital-intensive competition, and another pursuing broad-based, stability-oriented technological integration. The results of this test will show which system better transforms capital into lasting, system-wide advantage.

Another factor is that dictatorships don't suffer from the push-pull effect of election cycles, especially magnified in a two party state. Such polarization wastes a lot of energy and thus is an impediment to progress. But of course there is that small price to pay.

For the sake of friendly discussion (I realize this is tangential), my (unusual) take on China is:

Authoritarianism doesn't emerge for its own sake—it emerges when a population is politically engaged enough to threaten state control. China has a long history of mass mobilization and popular unrest: peasant rebellions, labor strikes, and yes, the events of 1989. This creates pressure for centralized authority. The United States, by contrast, has an unusually passive citizenry—low voter turnout, widespread political disengagement, and a culture that channels grievances into consumption rather than collective action. American "freedom" has been cheap to maintain because it's rarely exercised.

But when Americans do resist, what happens?

Consider Alex Pretti and Tank Man. Tank Man stood before a column of tanks and was not fired upon in that iconic moment. Alex Pretti stood with a phone, intervened nonviolently to protect a woman who had been shoved to the ground, and was shot ten times by federal agents while surrounded and pinned. One government showed restraint in its most infamous moment of confrontation; the other did not.

But the deeper contrast is in the aftermath. The Chinese government never claimed Tank Man attacked the tanks. The US administration, by contrast, immediately constructed an elaborate counter-narrative—claiming Pretti "attacked" officers and committed "domestic terrorism"—directly contradicted by multiple verified videos showing him holding a phone with his hand raised. The ugliness isn't just in the violence; it's in the brazen dishonesty that follows.

And this is not an isolated data point. Consider the broader picture: the US incarcerates more people per capita than any nation on Earth—2.3 million people, disproportionately poor and non-white, warehoused in a system that functions as social control while calling itself justice. Tiananmen was a visible atrocity. American incarceration is a slow, normalized one. Compare the casualties of a single crackdown to the bodies ground through American courts and prisons year after year, and ask which system has produced more human suffering.

Then add the architecture being built around it: the constitutional dead zone within 100 miles of any border, where Fourth Amendment protections evaporate. Masked federal agents operating in cities whose elected officials cannot stop them. Surveillance contracts expanding the state's reach into private life. A president willing to undermine the Federal Reserve for short-term political gain.

Meanwhile, China maintains tighter monetary policy, invests heavily in infrastructure and foundational technology, and takes a longer view of economic development. One can criticize its system on many grounds—but the American narrative of authoritarian dysfunction versus democratic flourishing looks increasingly like projection.

If you make a prediction that the stock market is about to collapse every year, then one year you will eventually get it right.

The market can remain irrational longer than you can remain solvent. But why do you think gold has tripled in price?

1. Mass hysteria.

2. Central banks rotating into gold to de-risk from USD combined with their usual slow bureaucratic processes. By the time they've decided that gold needs to be bought, the price has already run up by 50% and it's no longer a good idea to buy, but they still need to execute on their decisions anyway.

The USD isn't going anywhere for the simple reason that the USA can simply counterfeit any non-USD currency and there's nothing the issuer can do about it, whereas if anyone tries to counterfeit USD, they should expect a nice little missile to land inside their room no matter where they are in the world. "Reserve currency" status is entirely based on how effective the issuing entity is at taking care of counterfeiting.

North Korea is a prolific USD counterfeiter. Where are the missiles?

Digital currencies can't be counterfeit. China is cashless, so are some parts of Europe.

>Where are the missiles?

The scale doesn't seem to be large enough to warrant military action. It seems NK had mostly used it as pocket money for its embassy staff and has now stopped.

From https://en.wikipedia.org/wiki/Superdollar#North_Korea:

"The U.S. Secret Service estimates that North Korea has produced $45 million in superdollars since 1989. [...] Since 2004, the United States has frequently called for pressure against North Korea in an attempt to end the alleged distribution of supernotes. It has investigated the Bank of China, Banco Delta Asia, and Seng Heng Bank. The U.S. eventually prohibited Americans from banking with Banco Delta Asia. [...] The United States has threatened North Korea with sanctions over its alleged involvement with the supernotes, though it said those sanctions would be a separate issue from the nuclear sanctions."

>Digital currencies can't be counterfeit.

Yes they can. 51% attack.

I am about to give my take on software development:

Most [sane] software out there, but not all, has a main development time which is ridiculous compared to its life cycle (you could code in binary machine code, for several ISAs, it would not even matter).

Then, it is extremely hard to justify _HONESTLY_ a permanent income in software development. Really, really hard.

I'd be curious to know if this trend is unique to tech and the last 30 years

Or if you'd find it in previous industries that have had a huge influx of VC-like investors funding companies with the hope they'll at some point in the future be profitable.

When the unwind came, companies cut the layers that existed because hiring was easy, not because the work was essential. In a tighter market, the advantage shifts back to people with real systems experience and operational depth

Unfortunately, I think the next head of the fed is going to be appointed specifically to reduce interest rates, so we’re probably just going to go back to the 0-rate trough.

Quite likely. This will be great for growth.

.. and terrible for inflation, but that can be blamed on other people.

I don't see how this can happen, tbh. Like, the chair is just one vote, and the regional Feds have almost a majority. Presumably, whoever gets the job will say they'll reduce interest rates, but I don't see how they can actually accomplish this without getting the rest of the Fed on board.

Yes, it will, as always, be blamed on wages, even when wage growth is slower than inflation.

So we've moved on from blaming ZIRP and the pandemic to blaming AI?

Could have sworn I saw folks blaming the Amazon layoffs on the pandemic still yesterday

> The result is the worst of both worlds. European engineers now face US-level job insecurity with European-level compensation and limited mobility.

Firing people in most of Europe is still not as easy as it is in the US.

The opposite is also true, it's not that easy to leave your employer and you have to give 1/3/6 months notice before leaving, depending on your role/seniority/contract.

Sometimes companies even make you sign 12 months notice contracts clause where they pay you a fixed monthly bonus but you can't leave without giving a 12 months notice, my SO has signed one.

Indeed. It's not impossible to lay off people in Europe but they can't just say "you're fired!". There's a process and it costs time and perhaps 3 to 6 months of salary and you have to prove the layoff is needed. The business is incentivized to reduce hiring and find other work for the employee to do, instead.

To be fair, "you're fired!" doesn't happen in the US tech industry either. Even for performance-based firings, the employee almost always gets a few months of salary and garden leave in exchange for a release of claims. One of the positive effects of America being an overly litigious society. Unemployment insurance also kicks in.

> This is just false, firing people in most of Europe is still not easy.

Down sizing is a perfectly legal reason to fire people in Europe, and it happens all the time when big companies do mass firings. The difficult part is getting to choose which individuals to fire.

1. Most of Europe make it hard to do layoffs and most countries have different systems to prevent mass layoffs (including a state contribution to the salary, the Italian Cassa Integrazione is an example). Down sizing needs to demonstrate that you need real reasons for it, which implies demonstrating financial issues and lack of work and inability to reassign/retrain to different roles. Not easy.

2. American companies find every time that doing layoffs is very hard for them in Europe. Most recently Amazon, which, unable to lay off their people in Milan went through secondary tactics like demanding Return To Office (from people that signed hybrid or fully remote contracts) and other tactics involving mobbing or generous severance packages (up to 1 year in salary). Still, if the worker said no it was no.

I remember after the Brexit vote (i.e. years before anything actually changed) there was a rash of British companies who clearly would have gone bankrupt anyway blaming their ailing fortunes on Brexit.

There is remarkably little pushback on company narratives about layoffs or ailing economic fortunes from journalists which is weird because it's more normal that they are not truthful.

The Brexit vote is nothing like this though. AI is probably the biggest corporate gaslighting exercise I've ever seen in my entire life.

There were some remarkable claims made about Brexit. The best I can recall was a bus company closing a local bus route "because of Brexit", an year or two after the vote and therefore years before it actually happened.

Also very common to blame things on health and safety, GDPR, etc.

> The liquidity that flooded the tech sector didn’t just inflate valuations; it inflated teams, egos, and expectations.

Yes it's kind of obvious to anyone who's looking at the actual work being done: the constant churn of OS updates, the JS-framework-du-jour, apps being updated constantly...

It seems to me like a lot of this is just busy work, as if engineers need to justify having a job by being releasing inconsequential updates all the time. Bullshit jobs anyone?

I for one would really like things to slow down, we all deserve it!

Because it's important to recognize sometimes when someone you disagree with is right about something, I would like to note that Musk sacking most of the Twitter staff has not made the site unable to stay up. (The site has got worse for other reasons)

Westinghouse Electric Corporation built early electrical grid turbines, and worked extensively with consumer product markets to close the circle of demand. Accordingly, more retail products required more energy, and more energy required more turbines.

The LLM proponents are trying the same naive move with intangible assets, but dismissed finite limits of externalized costs on surrounding community infrastructure. "AI" puts it in direct competition with the foundational economic resources for modern civilization. The technical side just added a facade of legitimacy to an economic fiction.

https://en.wikipedia.org/wiki/Competitive_exclusion_principl...

Thus, as energy costs must go up, the living standards of Americans is bid down. Individuals can't fix irrational movements, but one may profit from its predictable outcome. We look forwards to stripping data centers for discounted GPUs. =3

"Memoirs of extraordinary popular delusions and the madness of crowds" (Charles Mackay, 1852)

https://www.gutenberg.org/files/24518/24518-h/24518-h.htm

There is some fat in the system that likely needs to cut off.

Here is Google complaint about not serving lobster biscue:

https://x.com/Andercot/status/1768346257486184566?s=20

Zero interest rate phenomenon.

This is likely the first time many have not experienced a widespread economic crash since 2008.

We could get another 2008-like market crash before 2030, once the major AI companies begin to IPO onto the public markets.

Reminder: this tweet could be totally made up.

Also lobster (or any other seafood) bisque isn't really expensive in the scheme of things.

Don’t think it needs to be either or.

ZIRP, AI, over hiring, and a wave of boot camp labour supply I suspect all contribute.

Plus we’re also likely approaching saturation on a lot of fronts with attention and ad density saturation. Things like YouTube seem to be on the edge of how much ads they can force feed without people just not using yt because it’s unusable. Enshitification isn’t a cycle, it’s a one way trip. Combine that with over hiring and it’s bound to hit a wall

But on the other side there are countless opportunities for valuable revenue-generating products that aren't based on dopamine addiction and/or ad tech.

It's a values problem, not an opportunity problem. Tech industry management is locked in a death spiral because it lacks the ethics or the vision to create real value, as opposed to extractive predatory value.

This applies equally to consumer relationships and employee relationships. The default value is "How can I screw these people over to get more of what I want?"

And that is - ironically - a failure of brain chemistry and emotional regulation.

Because making number go up is a catastrophic addiction in its own right.

> there are countless opportunities for valuable revenue-generating products that aren't based on dopamine addiction and/or ad tech.

Perhaps a bit of a hot take but I’d be inclined to disagree. The boom in big tech is I think almost exclusive driven by dopamine, brain rot and ad tech either directly or indirectly. Meta and Google - almost entirely ad funded. Netflix - binge watching and they’re trying hard to force more ads in. Apple makes the black rectangle to watch the content and ads - without the iPhone 1 doomscrolling wouldn’t be a thing. Amazon runs an ad empire, produces video content for binge watching and has a store designed to maximise consumerism and retail therapy.

Even the portions that are more infra like AWS - I’d bet a large portion of that fulfilling demand by things that are part of the attention/dopamine economy. All those TikTok dances aren’t served off a raspberry pi.

Don’t get me wrong not trying to discount tech as not having genuine ethical value or opportunities not existing. But the explosive growth seen in tech over past 20 years specifically is I think almost exclusively driven by adtech and attention economy.

And if that reaches saturation either this changes tracks to similar on AI or the growth plateaus. Other value creation certainly exists and is valid but I don’t see it filling the shoes of adtech.

Google and meta indirectly acknowledged the problem years ago already with their balloons over Africa to connect more eyeballs to the internet plan. If you can’t force feed more ads to current user base then you need more users. It’s telling I think that a wild plan like balloons in Africa was the plan selected, rather than going for the countless other valuable opportunities as you say. Speaks to the relative profitability

Personally I think all these posts miss 50% of the issue... I agree it's not AI, but I suspect it's only partially an interest rate story.

Tech changed a lot from 2010 to 2020. Prior to 2010 almost everything built required a huge amount of development effort, and in 2010 there was still a huge amount of useful stuff to be built.

Remember – prior to 2010 a lot of major companies didn't even have basic e-commerce stores because the internet was still a desktop thing, and because of this it really only appealed to a subsection of the population who were computer literate.

Post 2010 and post iPhone the internet broadened massively. Suddenly everyone was online and companies now had to have an e-commerce store just to survive. Only problem was that there wasn't a Shopify or even npm to build from... So these companies had to hire armies of engineers.

Similarly there was no Uber, online banking was barely a thing, there was no real online streaming services, etc, etc, etc...

During this time almost everything had to built by hand, and almost everything being built was a good investment because it was so obviously useful.

Around 2015 I realised that e-commerce was close to being a solved problem. Both in how most major companies had built out fairly good e-commerce stores, and also in how it was becoming relatively easy for someone to create an e-commerce store with almost no tech skills with solutions like Shopify.

I'd argue somewhere between 2010 and 2020 the tech industry fundamentally changed. It become less about building useful stuff like search engines, social media sites, booking systems, e-commerce stores, etc – these were the obvious use cases for tech. Instead the tech industry started to transition to building what can only be described as "hype products" in which CEOs would promise similar profits and societal disruption as the stuff built before, except this time the market demand was much less clear.

Around this time I noticed both I and people I knew in tech stopped building useful stuff and were building increasingly more abstract stuff which was difficult to communicate to non-technical folks. If you asked someone what they did in tech around this time they might tell you that their company are disrupting some industry with the blockchain or that they're using machine learning pick birthday cards using data sourced from Twitter.

I used to bring this up to people in tech but so many people in tech at this time had convinced themselves that the money was rolling in because they were just so intelligent and solving really hard problems.

In reality the money was rolling in because of two back to back revolutions – the internet and the smart phone. These demanded almost all industries made a significant investment in technology, and for a decade or so those investments were extremely profitable. Anyone working in tech profited from those no-brainer technical investments.

Post-2015 the huge amount of capital in tech and the cheap money allowed people to spend recklessly on the "next big thing" for many years. 2015 to 2020 was such an amazing time to be in tech because people were basically throwing money at you to build literally anything.

But time's up now. Companies are realising that a lot of the money they invested in tech in recent years isn't profitable and isn't even that useful. So now they're focusing in on delivering value and building up profit margins.

The tech market isn't broken, it's coming back down to reality. Like railway workers post the boom we must face that most of the core infrastructure has now been built. A few of us will stick around making the odd improvement and maintaining what's already there, but that boom isn't coming back. Many of us will need to seek new professions.

Great comment. I’m thinking along similar lines — what is there in tech to build? And the answer is, not much for the current cohort of services.

Big product companies with big products are solved problems in their respective fields. Building an Amazon or a Facebook is quite a lot of work. Maintaining it is much less work.

For a while the industry has done a thing where you do e.g. infrastructure in five different ways across ten different teams across three departments. It created a lot of “work” but it didn’t create much additional value.

Another instance of this was myriad “internal products” with the idea that some of them will be blockbusters because Paul Buchheit built Gmail as a 20% project in days of yore. That didn’t go so well, either.

You get the feeling that all this merry but ultimately futile kerfuffle was done to fuel the hype of growth but the actual job positions were completely uncoupled from revenue growth. For a time this was hard to see while global expansion was happening. Revenue was growing rapidly and so was headcount. It seemed to check out, arithmetically, but it’s not sensible. It doesn’t take twice as many workers to service twice as many employees in this industry.

When the global expansion didn’t have anywhere else to expand to and revenue stopped growing, the workforce-sustaining illusion fell apart. Now those companies are unloading everyone but the skeleton crew it takes to maintain the products. That’s a lot of people.

I mostly agree with your assessment of the industry. However, I think there are still more new and useful products to be built. They are not “the next big thing” though. Big tech Management has been screwing this up in a couple of ways though.

1. prioritizing bets for things that could be as profitable as social media or e-commerce instead of betting on more incremental improvement products.

2. Focusing on pricing everything with reoccurring revenue and thus increasing the lifetime cost for end users instead of selling products at a discrete costs and providing end users value

3. Optimizing for growth and controlling the vision of products instead of letting small groups of talented people slowly build products.

4. Treating people as fungible resources and moving them around all the time rather than letting people develop unique expertise skillsets.

As a result, any product that can’t achieve $10+ billion annual revenue within a couple of years with a ship of Theseus team is deemed a failure and scrapped.

Brother, the tech market is coming up to reality.

You and your good reasoning, but it means nothing to me.

Many of us will seek new a profession indeed: AI engineer. AI engineers mostly write code, but they are superior to software engineers...from the eyes of investors.

AI engineers mainly build abstract stuff: SaaS. They kill who the investors currently love the most: managers. 90% all managers will be replaced. 100 managers can be replaced with 10 managers and 10 security guards.

Then they kill 70% of the doctors, lawyers, and salesmen.

Then they kill 50% of the software engineers.

Then white becomes blue, and the eyes shift towards energy, transportation, and construction. The AI engineer, writes code like an AI, and notices these giant companies are sick. They can lobby all they want but the AI engineer and the AI lawyer will win.

Everybody who laughs now about software engineers being replaced has become serious, for the AI engineer has replaced the software engineer.

Let's see who is right in 2035. Your intelligence, or my fantasy.

I will add some commentary from my subjective POV in IT:

“Efficiency” is a damned lie. Enterprise IT is one of the most inefficient spaces out there, full of decades of band-aids layered atop one another in the form of fad products, fancy buzzwords, and “defining leadership” projects. The reason you cannot get shit done at work quickly isn’t because of bureaucracy or management layers standing in the way so much as it’s the vested interest in weakening IT and Ops teams so that those higher-ups can retain more of the profit pie for themselves.

My entire job is to make technology become so efficient that it fades into the background as a force amplifier for your actual work, and I’ve only spent ~1/3rd of my 15+ year career actually doing that in some form. I should be the one making sure documentation is maintained so that new hires onboard in days, not months. I should be the owner of the network and/or compute infrastructure the business needs to operate, not some MSP in another country whose contract you’ll replace with a lower bidder next year. I should be the one driving improvements to the enterprise technology stack in areas we could benefit from, not some overpriced consultant justifying whatever the CIO has a hard-on for from his recent country club outing.

Consultants, outsourcing, and fad-chasing aren’t efficient. They do not better the business, overwhelmingly. AI won’t magically fix broken pipelines, bad datasets, or undocumented processes, because it is only ever aware of what it is told to be aware of, and none of those groups have any interest or incentive in actually fixing broken things.

The tech industry is woefully and powerfully inefficient. It hoards engineers and then blocks them from solving actual problems in favor of prestige projects. It squanders entire datacenters on prompt ingestion and token prediction instead of paying a handful of basically competent engineers a livable salary to buy a home near the office and fucking fix shit. Its leaders demand awards and recognition for existing, not for actually contributing positively back to society - which leads to stupid and short-sighted decision-making processes and outcomes.

And all of this, as OP points out, is built on a history of government bailouts for failures and cheap debt for rampant speculation. There’s no incentive to actually be efficient or run efficient businesses, and this is the resultant mess.

I think you need some kind of source to back up the idea that IT or the software industry as a whole isn’t efficient.

Software companies have much higher profit margins than companies that ship physical products. There really aren’t many industries that do better margins than software.

To sell software, you don’t need a production facility, warehouse, nor do you even need an office building if you don’t want one.

https://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile...

…bruh. Literally the very first line:

> I will add some commentary from my subjective POV in IT:

Subjective is doing the carrying, there. I am admitting up front that this is specific to me, my career, and the specific life experiences I’ve had with it thus far.

Like…I won’t even entertain the rest of your comment if you’re not even going to read the entirety of mine before vomiting out an “UhM aHkShUaLlY” retort.

Well, from my subjective POV, the earth is flat.

The point of my comment is that a subjective anecdote from a very limited perspective isn’t telling a good story about why the industry is the way it is. You said these businesses aren’t efficient but they have extremely high profit margins, which objectively paints a different picture: they are sufficiently efficient. They are more efficient than most other businesses.

All this financial risk in the industry where employees are over-hired and low interest rate VC funds are thrown around haphazardly is accepted because even a modestly successful software business has high profit margins.

The investors that funded less than $10 million to Airbnb’s series A ended up a significant shareholder of a company that has the same market cap as PNC Financial Services in less than 20 years. PNC spent 180 years getting to that size.

Software-driven products have huge profit potential and they can grow fast.

If you think I’m being some kind of pedantic loser, fine, so be it. You can put the blindfolds on and ignore a data-supported viewpoint.

Gravity is coming back to Silicon Valley: workers are realizing that the Bell Labs image they were sold was mostly innovation theater and hoarding talent for websites overstuffed with ads designed to manipulate users into buying junk

The speculative nature of tech has always been present.

The point is mass media communication and frictionless money movements across the world and market access which is so freely availible to the small retail investor.

It's a recipe for disaster because an extraordinary claim can attract billions of dollars with nothing but hope and dreams to back it up.

Imagine if the Wright Brothers had today markets and mass media at their disposal, they'd be showered in billions or even trillions but the actual model didn't make any money because it was R&D

solid analysis but i think you're missing the logical endpoint here: this doesn't end with companies "relearning scarcity"... it ends with the permanent contractor-ification of various types of work at these tech companies (not just tech roles, but other types of roles at these companies). already, contractor-to-employee ratio has gotten higher and higher at these companies in recent years and I expect this to continue.

ZIRP (especially the "double tap" ZIRP in 2021/2022) created this monster (bootcamp devs getting hired, big tech devs making "day in the life of" tiktok vids).

contractors give:

instant scale up/down without layoff optics

no benefits overhead

no severance obligations

easy performance management (just don't renew)

this mirrors what other industries typically do after large restructuring waves ... manufacturing got temp agencies and staffing firms as permanent fixtures post-rust belt collapse. tech is just catching up to the same playbook.

Post 2022, tech CEOs decided that workers had too much power and needed to be brought down a peg, so they did layoffs and worked to get Trump elected to erode worker power even further. Just look at the leaked group chats with Andreesen.

> But in Tech, the playbook is different. Companies over-hire software engineers intentionally. To play the lottery.

The actual reason tech companies overhire is because people get promoted based on the number of people that are "under" them. All leaders are incentivized to fight for headcount.

> Europe just became a lower-cost extension of Silicon Valley.

Pretty much spot on. The UK included in the above definition of Europe as well.

Let's look at reality. In reality, warfare, k-shaped economic growth, and influential social media tantrums from Elon, POTUS, and other big billionaires are the más problemas stifling our job market. Go ahead and sit AI in last place as 'reasons' why the tech market isn't improving, but do not call it a scapegoat. We have many distinct problems here. A lot of them are not financial. It's a dumpster fire getting free heat, free fuel, and the oxygen supply has never been more pure. AI is simply the dumpster vessel putting it all together.

https://en.wikipedia.org/wiki/Fire_triangle

  > Till ~2010, a layoff was a sign of failure. It meant the CEO messed up.
  > 
  > In 2024, a layoff is a signal of “discipline.” Companies lay off thousands, and their stock price jumps.

Citation needed. Author started their career after 2010 so they are not basing that on personal experience. In my experience this is not true.

I am not OP. But to support his arguments.

CEO Failure News Example (2013): https://techcrunch.com/2013/08/06/fail-week-kevin-ryan/

'Stock Price Jumps' Example (2026): https://finance.yahoo.com/news/amazon-stock-jumps-pre-market...

Not sure if it is the articles I picked up, but the amazon example doesn't have a single mention of Andy Jassy!

It’s very easy to find examples of stock prices jumping after major layoffs going back may years, e.g. https://www.spokesman.com/stories/1996/jan/03/att-rings-in-y...

That article even says “ Wall Street, in keeping with its cheerful attitude about layoffs, […] investors bet that profit-sweetening job cuts, though perhaps not as dramatic as AT&T’s, would remain in vogue among large corporations.

Large layoffs have always been looked upon favorably by investors.

The industry was always a disaster, but if you take a disaster and put AI in the mix you get a disaster at light speed. It was always getting worse and worse but now it’s speedrunning it.

Computers are a lever, a force multiplier. If your process is shit, you can shit faster with a computer.

LLMs are another force multiplier. If your computerized process is a disaster … well, you said it and you’re right.

When I was young, the quote was still:

  To err is human, to really foul things up requires a computer.

That quote was on my mind as I wrote that message. I think I saw it as a child but some time after I had begun writing BASIC code. It took a moment’s thought at the time, but I soon came to realize its truth.

Not so much AI itself, but the billions invested into it and the hardware required - anything you invest billions into but that doesn't have similar return on investment is a fast track to an economic crash / correction. The Y2K tech companies are a previous example, investors were champing at the bit to invest in uh, pets.com or whatever but turns out it didn't / wouldn't earn enough money to earn it back.

I agree with the economic argument.

But I literally mean if you have a crappy business and put AI into it you’re just gonna make your business worse.

AI as a tool is not actually a solution for very much. AI can mark a good process better but it will also make bad processes way worse.

It’s a power drill upgrade when you were previously only using a screwdriver, but it’s still not a table saw.

>Europe just became a lower-cost extension of Silicon Valley.

Stay away from europe while you can.

IMO the issue is even more fundamental than the article presents. The software product market is approaching a saturation point. All the low hanging fruit has been commoditized, so buying something off the shelf is now generally preferable to having engineers on your staff. After the pandemic hiring spree, even the big tech companies realized they didn't have enough productive work for all these engineers. The effect is compounded by the return to normal interest rates, so investors are no longer desperate to dump their cash into every random startup idea. Ultimately, software engineers aren't going away, but the era of desperate need is over for good.

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