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I'm sorry, did everybody else not see this coming from miles away? This is the private equity playbook.

  1. Make a service so cheap as to seem to good to be true to attract customers.
  2. Gain a loyal base of people
  3. once theyre locked in, squeeze them for all they're worth.

When something is too good to be true, you ALWAYS have to be ready to either jump ship, massively change how you do things, or pay through the nose.

[-] JensSpahnpasta@feddit.org 25 points 2 days ago* (last edited 2 days ago)

Yeah - people are talking about replacing jobs with AI. As if it is not totally obvious that people like Sam Altman will totally bleed you dry after you fired all your workers. You will not save on your wage bill, you will simply give the money to Sam Altman

[-] KillerWhale@orcas.enjoying.yachts 10 points 2 days ago

Wages are treated as an immediate operational cost, while AI is framed as a capital investment. This accounting distinction makes AI look like a long-term asset, whereas labor remains perpetually categorized as an expense.

[-] jrs100000@lemmy.world 10 points 2 days ago

Only if you are running your own servers. You dont get to depreciate a SaaS subscription or metered bill.

[-] eleitl@lemmy.zip 2 points 1 day ago

And the servers are only useful for AI and they don't last long.

[-] sexy_peach@feddit.org 15 points 2 days ago

The angry devs from this article are idiots

[-] bilb@lemmy.ml 8 points 2 days ago

I have some sympathy for these people, but some don't seem to realize that Microsoft is not going to be upset over them leaving. They are not valuable to Microsoft as users. If they are unable or unwilling to pay now, Microsoft wants them gone. They are being shown the door. Making a post about deleting your copilot+ subscription or whatever is like bragging about being kicked out of a nightclub.

[-] BassTurd@lemmy.world 36 points 2 days ago

I've been preaching this for the past couple of years. Everything up until now has been entirely about gaining market share, and AI will never be cheaper than it is right now, and it's not cheap.

Just look at the "earnings" for companies like openAI. They are 1000+% in the red. It's impossible for them to change their sales model enough to make that profitable. As more data centers go up, the operating costs are also going to go up.

I've been telling people that now is the best time in the past decade or more to learn how to code. There will be positions available in the coming years when the only junior devs available are vibe coders.

[-] GoatSynagogue@lemmy.world 2 points 1 day ago

AI will absolutely be cheaper than it is now in the future, because you’ll actually be able to run it locally - look at the recently announced Nvidia powered Surface Ultra as an example of what’s coming.

Companies are trying to get their whole AI pipeline more efficient and “smaller” to reduce costs, because their costs to build and run data centres are astronomical. Where it will likely go is a subscription service to access their models that you run locally. Passes most of the cost on to consumers, and is recurring revenue which they all dream of.

[-] BassTurd@lemmy.world 3 points 1 day ago

I don't think there's a chance that happens either at the consumer level or mass adoption at the enterprise level. The estimated price of that nvidia surface ultra is expected to be around $3000. Only a handful of power users will pay that, and others may just buy it for the computer power. Right now for the basic user it's about $30 a month for basic AI plans. How many people that are willing to pay that do you think are willing to pay 100 years up front to then pay a subscription to then manage a local model?

Also, there are a lot of viable free models available right now that people can download for free. I have a recycled i5, 8gb ram machine that can run some basic models that are cable of doing 90% of the stuff the average person wants. My desktop with far better specs can run far more powerful models. The thing is, most people don't know these exist, and if they do they don't know how to set them up or are too intimidated to try.

That's just for consumers. Trying to host that at an enterprise level is much more difficult. Assuming the business has the tens of thousands of dollars of hardware to support 100s or thousands of users, configuring governance on LLMs and everything associated with enterprise management that is currently handled at the current companies will fall back on the business. That will probably require hiring specialist, or at least expanding the work force. If it takes 1 $3000, unreleased and untested laptop, imagine the cost to support a company, especially one doing software development.

Even with all of that, training the models isn't going to get cheaper. It's going to get more expensive as more data centers are built. Operating costs will go up, and unless these companies start charging upwards of 3k a month per user, they won't be profitable on AI alone. Obviously they are making money on other things like selling user data, but none the less, costs have to go up for even the notion of making money for these companies.

[-] MadBigote@lemmy.world 1 points 1 day ago

Care to elaborate on why we'd need more programmers? As of las year there was a "surplus" of them and they were purged from FAANGs and the rest followed suit. As of me, im about to get my degree in CS, but Im in my mid 30s and just got it for the lols, as j work in a difference field and the expectative of switching industries is not feasible in my country.

But i have a in-law getting her CS degree, and I don't see their chances of employment any morr positive than last the last year

[-] BassTurd@lemmy.world 3 points 1 day ago

I think that currently, a lot of places are replacing junior devs with AI. As senior devs retire or quit because of AI, there won't be skilled juniors to take those positions. It's my belief that there will be a vacuum left that needs to be filled by people that can code, not just use AI to vibe code.

I could definitely be wrong, but it's kind of cyclical like the dotcom bubble too. There was a surplus of devs, then a shortage. I think we're approaching the latter. If/when the bubble pops, we'll find out.

It's expensive to get a degree, but I also think having at least basic coding understanding both fundamentally changes the way a person thinks for the better and to be good, you have to have a good breadth of knowledge on computers and a wide array of different processes across different fields, so you become a more well rounded person.

Anecdotally, I pivoted from sys admin for a decade to full stack in my mid thirties. I was fortunate to have a connection that got me in the door, and it's been a lot of work starting over, but I've done it. You mentioned in your country that it's not feasible, but maybe if you can find an in somewhere or if the landscape changes significantly enough that unavailable positions open up, you might be able to catch a break.

[-] kescusay@lemmy.world 62 points 3 days ago* (last edited 3 days ago)

The unique thing about GitHub Copilot (and all the other vibe-coding tools) is that they're speed-running the playbook because this shit is not profitable. It can't be. Their costs scale up with usage, unlike every other business that can take advantage of economies of scale, so they've skipped the slow, steady enshittification phase and jumped directly into the "squeeze blood from this stone to keep the scam going a little longer" phase.

[-] BladeFederation@piefed.social 12 points 2 days ago

Good sign that it may be over soon.

[-] ripcord@lemmy.world 8 points 2 days ago

Absolutely 100% do not count on it

[-] HaraldvonBlauzahn@feddit.org 4 points 2 days ago

they’re speed-running the playbook because this shit is not profitable.

Wait, what? You say it is a scam? A kind of technical Ponzi scheme? A Madoff syndicate on steroids?

[-] pooterbroo@programming.dev 7 points 2 days ago

Plain inference is profitable actually, that's why there are a hundred inference providers on OpenRouter who compete by undercutting each other. The labs however aren't profitable because training the models is a huge drain.

[-] Cenotaph@mander.xyz 8 points 2 days ago

But they can only do that because others are doing traning, no? There's no point at which you can go "okay it's all inference from here", the model needs to be updated with new information/guardrails/context to continue being useful for most use cases

[-] kescusay@lemmy.world 4 points 2 days ago

As others have pointed out, the compute cost of inference is only one small part of the puzzle. All the frontier model providers - which OpenRouter gives you access to - are massively raising their prices in desperate bids to recoup the cost of model generation in the first place.

There's really no hiding from the token apocalypse unless you're running a model on your own hardware.

[-] chris@l.roofo.cc 5 points 2 days ago

In a vacuum maybe but are they profitable if you add the infrastructure investments to the mix? What about model development? There was a shit ton of money that was spent. Covering the running costs is not enough. At some point someone has to pay for the investments.

[-] CosmoNova@lemmy.world 28 points 3 days ago* (last edited 3 days ago)

I remember having to sit down my boss and explain how it can only become more expensive over time. It’s the big tech playbook after all. Didn‘t matter. I‘m told again and again how AI is only becoming stronger and cheaper. Especially during salary negotiations. Nasty stuff. They know I know it‘s BS and they still cling to this nonsensical narrative because it would be very beneficial to them and very bad for me.

[-] boonhet@sopuli.xyz 9 points 2 days ago

Open weight LLMs are actually pretty cheap because there are competing providers. But something tells me your boss isn't using openrouter to find the best price per million tokens lol

[-] pluge@piefed.social 20 points 2 days ago* (last edited 2 days ago)

The crazy thing is, this isn't really a "squeeze" in the traditional sense. The problem was that every single mainstream AI product has been heavily subsidized....because it's wildly expensive and not even close to being profitable.

That sort of subsidization was only going to last for so long. The dam is starting to crack. People aren't ready to pay what AI truly costs.

[-] badgermurphy@lemmy.world 8 points 2 days ago* (last edited 2 days ago)

And it doesn't seem like they ever will be. The LLM value proposition is already dubious at today's subsidized rates.

[-] binux@sh.itjust.works 13 points 2 days ago
[-] ptu@sopuli.xyz 7 points 2 days ago
[-] badgermurphy@lemmy.world 10 points 2 days ago

It reminds of any software made by any company that is at all well known. They are all operating from the same playbook.

[-] Valmond@lemmy.dbzer0.com 16 points 2 days ago

I didn't see it coming as I am on Codeberg 😎

[-] ripcord@lemmy.world 2 points 2 days ago

I mean you could equally be on github and just not use copilot

[-] Aneorthisio@lemmy.ml 14 points 2 days ago

The strategy is always to gain a monopoly or near monopoly on a market before pushing for the enshittification of the product to reduce costs and maximize profits, once customers have become dependent on said product, then pray that most choose the path of least resistance which is staying and dealing with the worse and more expensive version of what they're used to rather than retraining or restarting from zero elsewhere.

Capitalism 101.

[-] kurmudgeon@lemmy.world 11 points 3 days ago

The tactic has worked for drug dealers for decades

[-] HaraldvonBlauzahn@feddit.org 1 points 2 days ago* (last edited 2 days ago)

Also for example for the car industry.

Cars are addictive because if you don't have a car, and they are not common, you don't need one. But they are confortable, and this is what hooks people - our Naenderthal brain is wired to save energy and effort. Because cars are, at first, faster than, say, streercars, they are used more and more, and especially people use them for commuting. Because of Marchetti's constant, people use their daily time budget of about one hour for commuting in a car, and travel longer and longer distances. What results collectively is subururban sprawl, small shops in residential areas, as well as jobs nearby disappear and so on.

Once you are there, it is very difficult to go back, because daily distances are too large for streetcars, bicycles, and buses.

And to add insult to injury, cars stop to be fast once many people use them, since they need enormous amount of longitudinal space to be operated safely. This huge space requirement further accelerates sprawl.

Cars are an collective addiction, highly damaging. This kind of AI might become another.

[-] ripcord@lemmy.world 4 points 2 days ago

Admittedly, it's capitalism. But I just chose a negative entity.

[-] halcyoncmdr@piefed.social 4 points 2 days ago

This is going much faster than most private equity enshittification. That usually takes about 5 years to start. And has a system or hardware that makes switching painful. That doesn't apply here, it's easy to switch and almost a drop in change.

[-] badgermurphy@lemmy.world 6 points 2 days ago* (last edited 2 days ago)

They are burning money so quickly that they don't have the luxury of using the "slowly boil the frog" standard VC tactic, so they have to start the boiling before the frog is comfortable.

[-] IHeartBadCode@fedia.io 3 points 2 days ago

Human beings are terrible at balancing short-term gains for long-term consequences. It's mixed into our DNA. Our ancient ancestors, securing immediate calories or escaping a threat was a matter of life and death. Long-term planning wasn't as critical as immediate survival. Now do note, that's not an excuse for the people who foolish went head long into this.

This is why this struggle with the rich and powerful is eternal. It fundamentally taps on an ingrained flaw we collective fall for every single time. There is no one solution, there can never be one solution. People must forever fight themselves and the powerful from the exploitation of this fundamental flaw of humanity.

this post was submitted on 02 Jun 2026
566 points (100.0% liked)

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