- cross-posted to:
- technology@lemmit.online
- cross-posted to:
- technology@lemmit.online
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You mean you guys don’t rotate between 10 free accounts and use their monthly quotas?
That many free accounts is against their user agreement though hehe
What are they gonna do, close your accounts and make you sign up for 10 more? lol
I’m sorry, did everybody else not see this coming from miles away? This is the private equity playbook.
- Make a service so cheap as to seem to good to be true to attract customers.
- Gain a loyal base of people
- 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.
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.
It’s not even just private equity, this is more or less the exact strategy Microsoft uses.
Also reminds of Android
It reminds of any software made by any company that is at all well known. They are all operating from the same playbook.
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.
And it doesn’t seem lime they ever will be. The LLM value proposition is already dubious at today’s subsidized rates.
Pretty sure they picked the wrong tech to try and lock people into. It isn’t hardware and doesn’t have some kind of proprietary interface that takes time to get used to when switching. Some models might be better than others at specific things, but not enough to justify the prices they are going to charge for output you have to review and fix.
This is literally the easiest thing to jump ship from.
It isn’t hardware and doesn’t have some kind of proprietary interface that takes time to get used to when switching.
The proprietary interface is kinda the largest selling point, besides the once cheap prices. But the $10 plan going from 300 multi-hour prompts per month to 20 quick prompts per month effectively makes it worthless. Though, you could just pay a few hundred/thousand per month and continue, or bring your own API key from elsewhere, but at that point just use someone else’s interface. It’s not that much better than competitors and copilot isn’t offering anything unique.
It can still be pretty difficult to jump ship for any large corporation, but yeah there’s certainly harder things.
If you’re a pure vibe coder, this is literally 9/11.
That’s the stupidest thing about these AI companies’ valuation.
They don’t even really own anything!
Their models – their main proprietary IP – are not copyrightable or patentable, and not legally protected in any way. Any competitor can copy them at any time and then offer the same service for cheaper, without the overhead costs for training. The giants of the AI industry could easily be undercut and replaced at any time.
The hardest part about the copying is the actual copying without having access to the weights or even just a ready to run file for the model.
IIRC Deepseek kinda did something like that by asking ChatGPT tons of questions to train their own model or something
Yeah, you can do that … or some good old fashioned corporate espionage.
Or, hell, just ask ChatGPT for its weights model. With how shitty these AI companies are at security and guardrails, that might just work.
This is literally the easiest thing to jump ship from.
I’m not sure about that. We see professional developers complaining all the time when their AWS or GitHub account is banned. But this time we’re talking about vibe coders who have less skills than the average developer.
I believe that is largely their employers’ decision. It is easy to switch, but it is the boss who makes that decision, not the tech-literate team. Bosses like big well-known companies that can absorb blame so they can continue to cash their big pay checks even after failures that were clearly the fault of the 3rd party that no other bosses could blame them for choosing.
And they need to subscribe to access and execute their troubleshooting options.
All of them also bring their own comfortable export feature.
“I want to share all of this with my team. Create the prompt that is necessary to do this”
This is literally the easiest thing to jump ship from.
It depends how heavily you are leaning on ML tools to do business processes honestly.
It’s easy to implement something that mostly works and doesn’t need a ton of baby sitting, but moving from one solution to another is like rebuilding an ERP if you have gotten deep enough into the weeds.
This bubble is super scary though. The only things I can see propping it up would be world governments once the tech companies and other large enterprises halt spending. I don’t think the US can shoulder the costs and nobody else is gonna lol
Have you seen the IPOs and the rule changes that the stock exchanges and index funds made to please the AI overlords? It’ll be US pension funds left holding the bag when the bubble goes pop
astronaut meme.
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.
They are burning money so quickly that they don’t have the luxury of using the “slowly book the frog” standard VC tactic, so they have to start the boiling before the frog is comfortable.
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.
Good sign that it may be over soon.
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.
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
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.
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.
I didn’t see it coming as I am on Codeberg 😎
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.
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
The tactic has worked for drug dealers for decades
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.
Oops. Now that users are being to made to pay something closer to the true cost of AI inference, no one will like using it anymore. Could this be what ultimately sets off the bubble *collapse?
Users are paying way more than the cost of inference. Look up inference prices of high end open weight models vs claude or gpt. Cheaper by an order of magnitude.
It’s the constant training of new models that’s losing them money. New version is out every month.
To clarify, AI companies charging the cost that would make the inference profitable for them, against the operating costs and financing costs on new capital expenditures (new data centres, new compute and new model training*), is more than what most people appear to be willing to pay. That cost is indeed more than just the cost of inference incurred by the AI company.
*(I’m being generous and including model training as capex for the sake of argument, even if I personally think to continue the hypetrain, continuous model improvements are core to AI companies’ operation.)
Joke’s on them, I never used it. Fuck AI.
Single prompt takes 25% of the monthly usage in like 30 seconds even though I have Pro haha
Anyone planning to make a profit by billing this as metered is dreaming when agents suck down 40k tokens in a single prompt. I did the math, at like 0.2 cents a token that would still be 8k. No one is paying 8k for a single prompt. At 0.015, thats still 600 dollars. Its never going to make sense.
"For basically nothing’… If it’s basically nothing then use your damn brain to do it.
The 2 remaining devs using Copilot will leave it.
It’s rare to see such a clear example of first-mover disadvantage as GitHub Copilot.The company I work for had a pilot project for a while but recently they opened up for all users to order Github Copilot. Of course it is Github Copilot since everything else at the company is from Microsoft.
Honestly, only Tesla comes to mind. Maybe bleeding edge tech frontier is the one place where first movers RND cost is heavy enough to make it irrecoverable.
It’s interesting to contrast this w/ the field of medicine; RND cost can be recovered by squeezing the folks in the domestic market.
This is happening with GitHub because they resell other models, right? Including ChatGPT and Claude.
This hasn’t happened with the models directly on their platforms yet for the plans that still offer flat rates. Right?
At my company, all of us devs have GitHub copilot enterprise licenses, which was $39/month for basically unlimited use on most models. The new pricing is the same price except we get 3900 copilot credits a month. 1 credit is 1000 tokens. There is nothing concrete about how many tokens are used, but they estimate powerful models like Claude will use about 10 credits per transaction. The more basic models are less consumption, but still count. Code completion is still unlimited. It’s going to get really expensive really fast for companies balls deep in it.
For token context, we had someone come in and give us an hour long vibe coding lesson with Claude code.he created a basic 600 line app in that hour and consumed 40000 tokens. I have UI tests with twice as many lines of code. It’s going to be a blood bath, and I’m here for it.
Did you find a way to see how many of those credits you already used? To me it looks like they have completely removed access to that information from individual devs and only admins can manually generate reports containing it.
I haven’t. They just went live on the new model yesterday. When I read the release, it said there will be tools to monitor all of that. Whether that means they exist and I don’t know or they’re going to release them late and half finished in typical MS fashion is unknown to me.
I had talks with my lead and manager so they are aware. I have strong doubts that has been related to the people that need to monitor that. The company has been trying to push AI adoption for the past year, and we all hate it, so I’m not going to go out of my way to stop them from stepping on their own dicks. Hopefully a stacked unexpected bill would convince stakeholders to sit back and listen to those of us in the know. It won’t, but I’ve got my popcorn ready.
Yesterday I had a meeting where I explained this to my team. Nobody can use Opus anymore and shoot for under 5% of your monthly budget per work day. They better pray that I am the first one to run out of credits, I won’t buy more until that. From today alone it looks grim, they changed something in the harness too, making it burn credits. I would say we use it very lightly and we are in trouble. It is going to be a blood bath. Does anyone know if the JetBrains plan is more token efficient? I am also looking at just paying API cost for a cheap model on openrouter.
We don’t have any power users so I think we’re going to be fine for now. I do believe that by default all of your company credits are pooled, so one person could use everyone’s in theory. I thought I read that can be changed.
I’ve asked 3 questions to Claude today because I was struggling with an error. I’m curious to see how many credits I used to end up not using any of the generated code.
I change it to not be pooled. I am not going to used them conservatively for someone else to blow the entire plan on me.
What I want to know, is that are they just charging closer to the real cost or the actual real cost.
Chances are they would want to slowly increase the price à la boiling frog method.
And once that happens, then they have to increase it again to make profit, AND that has to measure up against regular ways of making money so it can’t just be barely profitable.
It’s a long road ahead for them
I was still using my copilot account, figured I’d see how the new pricing worked. I blew through 60% of my max+ limit in 1 day on absurdly light usage, promptly cancelled rather than upgrade from the $39 / month plan to the $100 /month plan.
I do think there’s a productivity help from AI but vibe coding everything is miserable and gives awful results. Targeted AI usage makes sense and I’ll refine my local AI usage and tooling for that.
Codeberg accounts incoming!
I don’t think they’re moving from GitHub, just GitHub CoPilot.
they should probably move away from plagiarismhub
That’s a non-existent distinction. GitHub is under Microsoft’s AI division.
https://www.techspot.com/news/109040-microsoft-ai-push-tightens-grip-github-after-ceo.html
They’ll move to another service, the service’s expenses will spike, and then that service will switch to usage based billing, and then they’ll have to look for another service again, and repeat the loop until they can run a good enough model locally.
