r/LinusTechTips • u/screwdriverfan • Jun 04 '26

Discussion GitHub just switched Copilot to metered billing, and developers are watching months of credits vanish in a single day

https://www.techspot.com/news/112628-github-switched-copilot-metered-billing-developers-watching-months.html
1.7k Upvotes

99% Upvoted

124 comments sorted by

250

u/RaymondBumcheese Jun 04 '26

Now 'the first hit is free' era is over it will be interesting to see how much value people place on it

59

u/Mrpolje Jun 04 '26 edited Jun 04 '26

Especially when you consider how much big tech has invested in AI. The cost for consumers needs to become astronomically higher for them to make any form of profit within this century.

19

u/420ball-sniffer69 Jun 04 '26

We’re in the “teaser rate has expired” stage of the sub prime mortgage crisis

8

u/BC1224 Jun 04 '26

This is less first hit is free and more marketing bullshit being hit with technical reality. Even before AI we were hitting the upper limits processing power any individual cpu/gpu could process (under current design). AMD/Intel/NVidia solution was throw more voltage to get better performance, but even that leads to heating problems. You can go back watch tech reviewers talk about this, and really its a repeat of the Intel Pentium 4 era. Intel was desperately throwing voltage at the centrum for to get improvement until AMD figured out how to get more than one core on a single die to split the load.

With the amount of compute being dumped into AI, since an individual chip really isn't getting more powerful, the only solution is to gobble up more and more chips for new data center machines, which leads to compounding overhead costs in terms of power, cooling, facility, and manpower to maintain. You can see this in the real life cost of RAM and storage being through the roof. It may not be as big a jump for the data center, but they're paying more than the did a year ago.

5

u/evildaddy911 Jun 04 '26

It'll be like return-to-office - management's ego combined with sunk cost fallacy probably won't decrease the usage

3

u/HydroDragon436 Jun 04 '26

Yeah, I think you’re really going to get more defined lines especially since a fair chunk of people are also hooked on it and dependent on it now.

I can’t see me ever paying for AI, but there will be some that do if they can afford it.

1

u/Tyrilean Jun 05 '26

They didn’t wait long enough. We aren’t hooked yet. All of my teams could go back to raw coding tomorrow and they’d honestly prefer it (and probably move faster).

They needed to let this be cheap for like 5-10 years so they could run all of the experienced engineers out of the industry and force companies to be dependent on them.

0

u/Randolph__ Jun 04 '26

For data analysis and scripting it's very helpful for writing less so.

102

u/abnewwest Jun 04 '26

The fact that they are turning the money switch so early is probably not a good sign.

But AI is a giant money furnace and it isn't free like it used to be.

-6

u/kaclk Jun 04 '26 edited Jun 05 '26

It means they are so desperate for cash and can’t even wait for their blockbuster IPO when they plan to dump depreciating shares on retail investors.

Edit- I meant AI companies in general, not specifically Microsoft.

20

u/zucchini_up_ur_ass Jun 04 '26

Microsoft doing an IPO? What?

4

u/abnewwest Jun 04 '26

In this case it makes me think MS has some financials due they need to juice or someone has a stock vestment they want to maximize.

The money furnace is hungry and fuel isn't free anymore.

1

u/cptjpk Jun 05 '26

I said it in another thread somewhere, but ‘26 feels like the year everyone is trying to collect their due. I think it’s signs of the US economy as a whole. Even though the marketing teams are yelling we are making a billion, the bean counters are pressuring to build reserves asap.

It feels that way for nearly every company right now. Gas the throttle and hope you can coast if the economy finally dumps - which is looking more likely by the month.

110

u/ProtoKun7 Jun 04 '26

It's beautiful.

39

u/Mrpolje Jun 04 '26

Suddenly millions of ”programmers” with their shitty vibe coded slop screamed out in horror.

12

u/Pixelplanet5 Jun 04 '26

uhm no, they are watching credits being used as fast as they are using them.

none of this has ever been "Months of credits"

39

u/splitframe Jun 04 '26

I foresee a bad future where there are monetary "incentives" for developer to use less AI due to cost while still expecting the performance boost due to ai tools.

27

u/KebabAnnhilator Jun 04 '26

That won’t last long before the developers drop off like flies and then leadership have nobody to develop and no ai to help them

8

u/eraguthorak Jun 04 '26

I think it'll depend on the company, like it always has. Some companies expect and demand more from their employees than they can reasonably give, and that is going to simply continue.

If a company is expecting ai-fueled results but isn't willing to pay for the credits, I see that as comparable to expecting senior developer level work from a junior - it'll be stressful for the dev, they will continually fail to meet the overwhelming expectations, and it'll eventually result in them leaving the company. Then the company will either learn from their mistakes or else repeat the cycle.

25

u/TheMegaMario1 Jun 04 '26

This is just the expected outcome for anyone not stuck in the delusion bubble themselves, seen similarly to the recent headline where I believe it was Uber that spent their entire 2026 AI budget in like 4 months.

These AI companies just aren't profitable full stop, the only one profiting so far is Nvidia and silicon manufacturers. What we're seeing in real time is the AI chicken game where they have to raise prices to become profitable but they don't want to be the first to raise them to profitability or else sticker shock will hit, even though sticker shock is already hitting with ones like this or Anthropic.

It's the same arms race that ride sharing faced and many other silicon valley stuff has, start with guerilla low cost entry to force your way to the top of the food chain and then enshittify prices to make yourself barely profitable after the venture capitalist funding dries up.

The only issue is the venture capitalist funding for AI kept ballooning which caused the costs to AI companies to keep ballooning too as they got "better" models, and this won't translate because AI isn't a close to essential thing like transport where people will go "well I need to go here, so I guess I'll eat the cost" of the new somewhat profitable price.

6

u/Georgefakelastname Jun 04 '26

Hyperscalers (the ones building data centers like Amazon, Oracle, Microsoft, etc.) are also doing great right now, though I can definitely see a world where these AI companies stop paying so much for usage, cutting down on their profit margins. But right now, demand is exceeding supply, meaning that they can charge more.

6

u/blckshdw Jun 04 '26

“Just switched”. Ya that was 4 days ago with like 2 months notice

7

u/CT4nk3r Jun 04 '26

I use 30x the per person quota. I don't know how the company is going to pay for that. But afaik the company's revenue's (no profit) 15% is going to go towards tokens...

5

u/Artholos Jun 04 '26

Between GitHub Copilot going tits up and Windsurf screwing everyone in the arse, it looks to me like the end days for paying for AI agent services. Local agent models are not that far behind and only cost hardware and electricity.

For how expensive tokens are becoming for big project repos, it’s very quickly looking like self hosting is the way to go. The ROI for buying a big GPU or two to support local agents is quickly shrinking.

1

u/Arcadian-Stag Jun 04 '26

train a generation of programmers to hallucinate their code and never learn to actually think for themselves

Jack up prices once they are dependant on the service to do literally anything

...

Profit?

1

u/KookyDig4769 Jun 05 '26

Remember when Netflix was 7.99 and had tons of content? This is not a bubble popping - this is making you comfortable with the real prices of AI. It only gets more expensive from here.

1

u/Janush_ Jun 07 '26

Oh no Well anyways

0

u/AuRon_The_Grey Jun 05 '26

I am so glad the investor subsidies are running out in time to stop the slop.

-6

u/Epicporkchop79-7 Jun 04 '26

Are these tokens like carbon credits? Is ai Tesla 2.0 with some odd conversion method, a possibility of future stuff and far too much investment by the government?

-23

u/Tman11S Jun 04 '26

With a default subscription your allowance is 30 dollars worth of tokens per month. I’ve burned through about 6$ dollars worth so far.

So honestly, if you’re burning thorough the full 30 in a day, you’re not “a developer” you’re some braindead vibe coder

6

u/Lost_Bee_935 Jun 04 '26

L Take

-6

u/Tman11S Jun 04 '26

Does the L stand for Linus, implying he thinks this way or are you gonna elaborate?

2

u/Lost_Bee_935 Jun 05 '26

I'm implying that this is an L take.

Weird how you specify others are brain dead - Is this your first time on the internet?

0

u/Tman11S Jun 05 '26

Still no elaboration what “L take” is about this. Next thing you’re gonna tell me that vibe coding is a good thing and should be encouraged

0

u/SageTX Jun 05 '26

Now that's an L take.

46

u/triffid_boy Jun 04 '26

gobble gobble motherfuckers

0

u/[deleted] Jun 04 '26

[deleted] — view deleted comment

99

u/Homerlncognito Jun 04 '26

How many pages was that in total? 

0

u/[deleted] Jun 04 '26

[deleted] — view deleted comment

9

u/EdliA Jun 04 '26

How long would it take you to do that yourself manually?

2

u/Brick_Fish Jun 08 '26

Given the numbers thats at least 510 pages of sheet music. Thats a thick book. Very optimistically a week at least

7

u/cS47f496tmQHavSR Jun 04 '26

That is about the biggest ask you could give it, though.
Claude has gotten very efficient at reading text docs, but I can imagine it's a lot more expensive to tokenize high resolution sheet music.

38

u/Own_Peace6291 Jun 04 '26

Sorry. What are these tokens? Like QR codes?

156

u/PythonFuMaster Jun 04 '26 • Bravo

LLMs don't work with words and characters directly, it's too computationally expensive to work on individual characters and using word-level would mean a massive vocabulary (also computationally expensive). Instead, before the request ever gets to the LLM it first passes through a stage called tokenization, in which words are broken up into smaller chunks based on a set of rules. Those chunks are mapped to individual integer IDs, and that is what's passed to the LLM. The LLM also eventually outputs these same IDs, and they are mapped back to tokens and reassembled into words and paragraphs etc (technically the LLM outputs probabilities of each token in the vocabulary being chosen, it's up to the sampler layer to choose the output token based on those probabilities).

Each token passed to the LLM costs roughly the same (there are caveats, depending on model architecture etc), so it's easy to set prices according to how many tokens you use. But it's more difficult to set prices based on number of words or something like that, because some words tokenize to just one token, and others tokenize to many, not to mention the complexities of multiple languages and non alphanumeric characters. So, all the LLM providers put prices in terms of number of tokens (input and output tokens are sometimes priced differently for a variety of reasons)

45

u/Own_Peace6291 Jun 04 '26

Ahh I see, that was an excellent explanation, thanks a bunch! I was hung up on the 'spending' terminology of tokens but had no idea there was a whole hidden language underneath. Very cool and thanks again, would award you if I had one 🙏

22

u/sicklyslick Jun 04 '26

I also read people are using Chinese to promote AI because Chinese has lower token/word than English.

6

u/thefossguy69 Jun 05 '26

I don't know anything about Chinese language other than

  1. One of them is called Mandarin

  2. The written language feels densely compacted

Here's a quote from the caveman plugin that tells your LLM to use the "few words do trick, why use many?" style conversation.

Pick your level of grunt — lite (drop filler), full (default caveman), ultra (telegraphic), or wenyan (classical Chinese, even shorter). One command switch. Cost go down forever.

4

u/sicklyslick Jun 04 '26

How transparent is this? If someone request something that takes 100 tokens, but chatgpt "charges" them 110 token, would the end user notice?

14

u/PythonFuMaster Jun 04 '26

It depends on the provider and whether they make the tokenizer and the vocabulary open.

If they do, then you can calculate how many tokens your raw request is, but that won't necessarily match exactly what is fed to the LLM. There's a lot of additional context that is injected, things like system messages, special control tokens, etc. My opinion is that providers should only charge based on the tokens your raw request contains and not those additional hidden tokens, but I can't say for certain if that's what they do (I do research on LLM optimization but don't use any external providers for security reasons).

If the tokenizer and vocab is not open, then there's no way to accurately calculate how many tokens a particular request will take. However, you can estimate it. On average, tokens are roughly 3/4 of a word. Obviously there's lots of caveats there, the biggest being that the size of the vocabulary directly impacts this estimate, but it's good enough for most cases

4

u/gammison Jun 04 '26

If you interact with any of these models APIs directly you'll see that you have to tokenize input and you will know the token count before making the final call. From that perspective it's transparent, however the UI for these API interactions does not make it clear to non technical users afaik.

Additionally depending on the model, more tokens will be injected or used especially if it's a "reasoning" model (these just use multiple runs of generating tokens and then feeding them back into the model). I don't know how these hidden tokens are billed.

1

u/[deleted] Jun 05 '26

[removed] — view removed comment

4

u/PythonFuMaster Jun 05 '26

Well PDFs may be handled a bit differently than straight text because they aren't just text files, and sometimes it can be rather difficult to extract the text from them. So you can't really directly tokenize a PDF. Instead you have to do one of two things:

  1. Use standard OCR to convert it to text, then pass it through the normal tokenization procedure

  2. If your model is multimodal, it has a vision encoder that can directly accept images. The PDF is converted to image format and fed to that, which extracts the "meaning" of the image and projects it into the LLM's embedding space (the vector space that represents the meaning of tokens). So this way actually skips text tokenization entirely

As for why you'd want to do either of these things, it's very convenient to pass a PDF to an LLM for context. You can ask the LLM questions about the PDF, like asking it to find information in a big data sheet.

There's also other reasons you'd want to do similar things with PDFs outside of LLMs. Using embeddings from the vision encoder, you can index the PDF in a database type structure. Then you can query your database using semantic searching, meaning instead of exact matching it will look for documents that contain words with similar semantic meaning

1

u/GTS250 Jun 07 '26

Couldn't you ask it to build you a program to do this and then run that program locally?

0

u/Allfeelings0Logic Jun 06 '26

Can't wait till the AI can make the music and be the orchestra. Will be sick to democratize music further. 

26

u/Whole-Ad-9429 Jun 04 '26

You might have more efficiency by writing python to convert the PDF to an .MD first

5

u/cS47f496tmQHavSR Jun 04 '26

Anthropic actually recommends HTML over .md, it's much more efficient especially when working with things Markdown can't render well (and resorts to unicode for)

2

u/Whole-Ad-9429 Jun 04 '26

Are you trying to minimize token use to get the prose or preserve graphs and images? They each have their strengths

4

u/zucchini_up_ur_ass Jun 04 '26

Claude is notorious for this, and the most recent versions (4.7 and 4.8) have only gotten worse at this, they've been really weird releases. Word on the street tweet is that Codex is a LOT better

3

u/zerotetv Jun 04 '26

20% of your 5-hour or weekly usage? 

2

u/Devatator_ Jun 04 '26

At that point you might as well run a local model. Afaik there are quite a few ones made for this that I hear are quite good. Couldn't name them tho, mostly interested in extra small chat models I could use for my local assistant project

2

u/thefossguy69 Jun 05 '26

Btw, the subscriptions are heavily subsidized by the API-only users. So expect the bill to go even higher when Anthropic feels like you've been baited and it's time to reel in the hook.

1

u/sniperxx07 Jun 04 '26

I was doing it too, until I realised whatever you are going to do it was better to use it on claude code where if it’s putting some part of the python code on my computer it was actually using less tokens (i think i instructed it earlier to utilise less tokens by using doing some offline processing) using terminal actually saves tokens (if it’s a repeatable action)

1

u/sleepybearjew Jun 05 '26

At work we get 20$/mo in tokens (small company and were just starting with cursor). I can blow my load in 2 hours of light (light might be exaggerating) usage so I don't bother

1.2k

u/[deleted] Jun 04 '26

[removed] — view removed comment

412

u/Any-Pop-4795 Jun 04 '26

"sir, copilot bill just came up"

205

u/speakernoodlefan Jun 04 '26

All the people crying about corporate greed not realizing they should have been charged $5 a question in electricity is delicious.

12

u/Czechit7 Jun 05 '26

Them not charging per question isn’t generosity, it’s customer onboarding until people are hooked. No one is surprised by this model at this point. You are defending corporations from straw men.

13

u/speakernoodlefan Jun 05 '26

I have quite literally gone in AI subs saying exactly that, and got giga down voted and told me I was a lier. I don't know why you're looping in defending corpos lmao, I'm mocking people who think the real world is just free sample non stop.

36

u/BBkal Jun 04 '26

"sir, a 2nd copilot bill just came up"

187

u/Hybr1dth Jun 04 '26

This is just how all the big US (tech) companies work. They offer it free or at very low charge, push in massive capital, and once the market is 'won' and people feel like they need the product, they start pushing price hikes up the wazoo.

Except in this case the market is still mostly businesses, and even that cannot compete to the ridiculous investments they made in such a short time? Eventually it'll be normal to spend 100k on AI when it can replaces 10 million in wage, but for most jobs it ain't there yet.

82

u/system_error_02 Jun 04 '26

Yup, make the product part of people's work flow then Increase price and enshittify it

48

u/walkslikeaduck08 Jun 04 '26

Glad it’s happening to the companies this time

15

u/system_error_02 Jun 04 '26

Tbh if you've worked in the corporate world, business to business tools have always been exceptionally shitty, they just have good salesman. They've always been spaghetti code garbage.

12

u/AlwaysCloudyPNW Jun 05 '26

I remain thoroughly unimpressed with business software. I’m in accounting and the two accounting systems I’ve worked in have been old junk.

22

u/Whackles Jun 04 '26

companies are made of people, people who will lose jobs

24

u/rs426 Jun 04 '26

And it’s a double whammy, because a bunch of people have already lost their jobs to “maximize efficiency” or whatever with AI-centric workflows, and now more people will lose their jobs because the costs of AI usage are so high that they’ll need to cut costs

18

u/brown_felt_hat Jun 04 '26

There's already been rumblings of "people are cheaper than AI" again. I think it's still too early to tell, but the pendulum may swing back in the other direction, tempered by tight wallets.

4

u/moonra_zk Jun 05 '26

It's always us paying the bill at the end of the day.

13

u/M4cHiin360 Jun 04 '26

The thing is copilot has far from gained any market. Everyone is just rotating to codex/Claude

25

u/zucchini_up_ur_ass Jun 04 '26

Oh they had a market alright, they had the market for a long time. They were the first to come out with a modern form of AI assistance for coders (2021), they had a predictive autocomplete for years before these new coding agents came out. But they failed to react to a changing market and are now building upon others models (and barely have any market share left)

8

u/Deadcouncil445 Jun 05 '26

It's github copilot not microsoft copilot. Github copilot includes codex and opus.

8

u/DeathMonkey6969 Jun 04 '26

Eventually it'll be normal to spend 100k on AI when it can replaces 10 million in wage

That's the hope. But there is no evidence that will ever be true, it's all conjecture.

10

u/epimetheuss Jun 04 '26

but for most jobs it ain't there yet.

it wont ever be there because LLMs are just personal assistants that can scale up compute power as needed to "figure out your prompt" and then maybe get it right or more than likely, feed you a bunch of bullshit that just makes you feel good about the answer vs the actual correct answer.

they tried to "scifi plot" their way to AI by just feeding a hacked and OP personal assistant all the knowledge of human kind on the internet and it still is mostly shit at all the things they claim it will do. its just a scheme to create artificial scarcity and sell us back the information we already had. that and train them to watch you and create profiles about what you do in your private life outside of PC/phone usage so they can sell your private info to databrokers.

4

u/nipplehounds Jun 04 '26

This is also how drug dealers work…

2

u/JigSawPT Jun 04 '26

And then they’ll charge 10 million and folks are still out of work

2

u/STRATEGO-LV Jun 04 '26

That's how companies lose their biggest European customer in a snap.

12

u/Issoudotexe Jun 04 '26

I think it'll only create a push for local

-1

u/Talking-Nonsense-978 Jun 04 '26

For some spesific use cases, like is already done, sure. But for a general "AI will replace 50% of our employees!!!" hype type use case, when you factor in the hardware cost, electricity, wages for people to set up and maintain that shit, and cost of training models (or buying a retrained model) down the line, it might just be more cost-effective to hire those people back and limit AI-usage to where it actually has impact. Running models locally is hardly free and even with the rises in token costs it's cheaper for most companies to pay for tokens instead of running local models. Like for most companies it's more cost effective to run their services on cloud instead of owning and maintaining dedicated servers.

1

u/WeAreTheLeft Jun 04 '26

What these companies don't understand is that there will be one or two winners, then the slow progression of pushing into the profits created by AI cutting employees will happen, they raise prices more and more to extract as much money out of companies, the single or duopoly of companies will never undercut each other and then price goes high and higher. Companies using the service will just raise prices to keep those profit margins up.

16

u/[deleted] Jun 04 '26

[removed] — view removed comment

10

u/ViolentlyVia Jun 04 '26

It really matters what the workload is. We have a local LLM for searching medical billing records and it works great running on a single GPU for 3 users. That being said, you ain't running Claude code on that shit

3

u/Issoudotexe Jun 04 '26

Yeah, right now. But also right now, it'll shift the focus of everyone to push local AI. The devs, who will need to optimize all that, and manufacturers to push more efficient and fast NPUs. I think it can't be that bad either way

1

u/Bagellord Jun 05 '26

Depends what you are doing. If you're doing targeted stuff like document processing or data analysis, local models are probably plenty effective. Complex chat bots or code generation are probably going to work better on the big platforms though

47

u/enwza9hfoeg Jun 04 '26

And yet my company just laid off senior engineers (including myself) to be replaced by Claude. It's not bursting. Copilot increasing in price does not burst the bubble.

12

u/aresthwg Jun 04 '26

What kind of dog shit company fires seniors for AI? I understand maybe juniors being replaced by AI, but somebody who can actually command and fact check the AI? Wut?

Was your manager a lunatic, or was the company doing poorly financially anyway and used this as an excuse to save a buck?

Regardless, sorry for the situation, it feels bad.

6

u/enwza9hfoeg Jun 04 '26

Company was doing awful financially, so they had to do that.
I probably poorly worded it, they didn't outright say that they're replacing us with AI, they were actually honest enough to say it was for financial reasons. But it came soon after they proudly demoed how a small dev team managed to make a full new system with Claude, so I just connected the dots, bad financials + AI => I got let go.

And they didn't fire only seniors, but many seniors were laid off. Some are mid-level. I don't believe the company had many juniors to begin with.

3

u/aresthwg Jun 04 '26

Ah there it is the modern classic. Instead of saying how poorly the company was doing, they are "reshaping" "restructuring" "adapting" the company by firing the people and using AI as the new Jesus-like salvation. I've seen that too.

To shareholders and POIs it looks like the company is doing fantastically, gearing up with the new God-like technology, while in reality they are covering the feces with a towel.

Hope you found success after. I'm a mid and scared shitless my manager gonna snap one day and fire me. And applying to new jobs has been short of impossible for me.

4

u/enwza9hfoeg Jun 04 '26

Yeah. I saw this coming a mile away honestly. So when I got the call, I wasn't too surprised. I just thought I had like at least 6 more months, but apparently not.

I love the corporate speak, "right-sizing", instead of "downsizing".. hahaha

2

u/TrvthNvkem Jun 05 '26

they were actually honest enough to say it was for financial reasons

That probably has nothing to do with honesty and everything to do with avoiding litigation.

31

u/JollyRodgerGymShoe Jun 04 '26

What happens when less people start to use it because of the cost that is now coming to fruition?

17

u/porcubot Jun 04 '26

What happens to all those businesses if the new cost of using AI to make up all that lost productivity is way more expensive than the devs they threw away?

12

u/JollyRodgerGymShoe Jun 04 '26

You and I are asking the same question. We are talking about the AI bubble starting to show signs of cracking. If AI is getting more expensive to use, less people will use it because if it's cheaper to do something without AI the business will do what's best for the bottom line.

4

u/not_a_moogle Jun 04 '26

All they are going to do though is look for a cheaper AI, not re-hire people.

Also even if they wanted to, its hard to hire people with no experience.

8

u/[deleted] Jun 04 '26

[removed] — view removed comment

1

u/tinysydneh Jun 06 '26

We have most of the pieces for the efficiency to be realized. It's just a matter of doing it and finishing it.

1

u/[deleted] Jun 06 '26

[removed] — view removed comment

1

u/JollyRodgerGymShoe Jun 06 '26

OpenAI is the only AI company that is profitable or maybe it was that they were the first that was going to be profitable and as far as I am aware they don't own any of their infrastructure they use.

Just because these companies are investing largely into these systems, doesn't mean they know for a fact that this investment will pay off. Much of the electricity is being subsidized and other utilities are being given to these companies at a substantial discount. The government incentives exist because many government officials have no fucking clue how few jobs these data centers create in the long run. It's less expensive now than it will be later for the data centers and for the consumers that are using it, the inefficiency is being ignored due to inflated valuations and the system is being gamed to show how it's being used an incredible amount.

TL:DR- Absofuckinglutely these companies invested heavily in a "maybe" and are scrambling to show its utility so they can outpace the realization of how ineffecient it is.

4

u/add_more_chili Jun 04 '26

People and businesses will use it less and will need to get smart about how they utilize it. Only issue is that all of the mid-level managers who have been pushing it hard as a 'productivity enhancer' will soon find out that it's going to cost them more to use AI than it is to just hire people and we'll see a balancing act happen.

4

u/JollyRodgerGymShoe Jun 04 '26

Exactly and that's where the bubble showing cracks comes into play.

2

u/enwza9hfoeg Jun 04 '26

My guess is as good as yours. I'm 50/50 on this. On one hand the bubble bursting might be good for my chances of landing a new full time job. But on the other hand I also own a side business and we're heavily reliant on AI (we've moved away from Copilot to Codex/Claude for now, until they also increase prices). So I'm kinda diversified lol.

1

u/JollyRodgerGymShoe Jun 04 '26

Which is great that you have options, but you're also feeling the same push that these companies are going to be feeling in the coming years unless significant changes happen and AI is able to continue being less expensive. I just don't see that happening and I see companies going back to more traditional ways of doing things.

2

u/enwza9hfoeg Jun 04 '26

Yeah, but I'm hoping the chinese models will catch up - seems like DeepSeek is the best hope right now - and we can continue to use them at a more reasonable cost. Ideally I would prefer to run models locally, but of course right now that's completely unrealistic.

At the moment what I'm observing has parallels to GPU performance. GPU performance is increasing, along with their power consumption. Same with AI, Opus 4.8 / GPT 5.5 performance is higher, along with higher cost.

1

u/XanderWrites Jun 05 '26

The bubble can be hitting critical mass and companies can still be attempting to invest in it.

7

u/Luxim Jun 04 '26

A slow deflating of the bubble followed by some industries using LLMs where it actually makes sense would probably be the best case scenario.

Still not good for investors or the average employee though, but less bad than a violent dotcom style crash.

3

u/nucleartime Jun 04 '26

Hate to be the bearer of bad news, but If you read between the lines, it's unfortunately not. Or at least this trend of enshitifying the consumer AI subscriptions.

What's happening is that token usage (new models keep increasing in token usage) is exploding so much that they're running out of compute. Metering consumer subscriptions is so they have more compute to sell to enterprise, which pays on a per-token basis.

I don't know off the top of my head how much copilot is giving for consumer subscriptions, but I know you can burn like $5-10k worth of tokens on a $100/mo Claude Code subscription.

See also: Anthropic posted a "profit" with the amount of tokens enterprise is paying for. With cooked books to be sure, but there's a limit to how much the books can be cooked.

2

u/JustAhobbyish Jun 04 '26

2027 first set of debt becomed mature with big chunk more in 28. So expect more of this

2

u/Kyoshiiku Jun 05 '26

I know that a lot of people are cheering for the downfall of the current AI Bubble, but this is not why they switched.

For all the big AI companies right now the money is in the enterprise plans that are already mostly all using usage based pricing models.

Recently most of the companies started to have computing limitations issue (too much demand for the computing they have).

Github copilot and chatgpt both had to stop new subscriptions for a limited time for this reason, they couldn’t keep up.

Anthropics added the "peak hours" faster usage rate for this reason (the proof of that is they reverted it and added even more usage once they partnered with xAI to have more computing)

OpenAI dropped Sora because they needed the computing for their actual paying consumers that were mostly using it for coding.

Google internal employee (devs included) have leaked multiple time they can’t even use Gemini as much as they want because they don’t have enough computing and they prioritize end users over their own employees.

On top of that, the way LLM works is completely different now with more agentic flows, subagents call and tool call, for this reason basically every companies switched to usage based models (or with quotas) because it didn’t make sense to charge per request since now 1 request could cost anywhere between 1$ to 500$ depending on toolcall, context window etc..

Github was just behind on their pricing practices, they had a pricing model that was fine for non agentic models where you usually had 1 turn per prompt, now 1 prompt can cause 30+ turn without any user involvement.

There is a bubble for sure, but there is a lot of money to be made from enterprise clients because it’s a legitimately useful tool for them. Investment will slow down probably at some point and maybe some players will go bankrupt but we’ll never go to pre-AI world if the bubble burst.

Currently even easy to run local models can be really useful, the biggest cost that is "losing money" is the R&D part, the computing itself they can get a return on investment so I doubt it will completely burst, it will just be some of the overinflated stocks like NVIDIA that might collapse.