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I'm confused with your second point. LLM companies are not making any money from current models? Openai generates 10b USD ARR and has 100M MAUs. Yes they are ru

I'm confused with your second point. LLM companies are not making any money from current models? Openai generates 10b USD ARR and has 100M MAUs. Yes they are running at a loss right now but that's because they are racing to improve models. If they stopped today to focus on optimization of their current models to minimize operating cost and monetizing their massive user base you think they don't have a successful business model? People use this tools daily, this is inevitable.

airstrike 1y ago
No, because if they stop to focus on optimizing and minimizing operating costs, the next competitor over will leapfrog them with a better model in 6-12 months, making all those margin improvements an NPV negative endeavor.
bbor 1y ago
It’s just the natural counterpart to dogmatic inevitabilism — dogmatic denialism. One denies the present, the other the (recent) past. It’s honestly an understandable PoV though when you consider A) most people understand “AI” and “chatbot” to be synonyms, and B) the blockchain hype cycle(s) bred some deep cynicism about software innovation. Funny seeing that comment on this post in particular, tho. When OP says “I’m not sure it’s a world I want”, I really don’t think they’re thinking about corporate revenue opportunities… More like Rehoboam, if not Skynet.
- dvfjsdhgfv 1y ago
  > most people understand “AI” and “chatbot” to be synonyms This might be true (or not), but for sure not on this site.
  - bbor 1y ago
    I mean... LLMs have not yet discovered a business model that justifies the massive expenditure of training and hosting them, The only way one could say such a thing is if they think chatbots are the only real application.
mc32 1y ago
Making money and operating at a loss contradict each other. Maybe someday they’ll make money —but not just yet. As many have said they’re hoping capturing market will position them nicely once things settle. Obviously we’re not there yet.
- colinmorelli 1y ago
  It is absolutely possible for the unit economics of a product to be profitable and for the parent company to be losing money. In fact, it's extremely common when the company is bullish on their own future and thus they invest heavily in marketing and R&D to continue their growth. This is what I understood GP to mean. Whether it's true for any of the mainstream LLM companies or not is anyone's guess, since their financials are either private or don't separate out LLM inference as a line item.
Forgeties79 1y ago
> that's because they are racing improve models. If they stopped today to focus on optimization of their current models to minimize operating cost and monetizing their user base you think they don't have a successful business model? I imagine they would’ve flicked that switch if they thought it would generate a profit, but as it is it seems like all AI companies are still happy to burn investor money trying to improve their models while I guess waiting for everyone else to stop first. I also imagine it’s hard to go to investors with “while all of our competitors are improving their models and either closing the gap or surpassing us, we’re just going to stabilize and see if people will pay for our current product.”
- thewebguyd 1y ago
  > I also imagine it’s hard to go to investors with “while all of our competitors are improving their models and either closing the gap or surpassing us, we’re just going to stabilize and see if people will pay for our current product.” Yeah, no one wants to be the first to stop improving models. As long as investor money keeps flowing in there's no reason to - just keep burning it and try to outlast your competitors, figure out the business model later. We'll only start to see heavy monetization once the money dries up, if it ever does.
  - Forgeties79 1y ago
    Maybe I’m naïve/ignorant of how things are done in the VC world, but given the absolutely enormous amount of money flowing into so many AI startups right now, I can’t imagine that the gravy train is going to continue for more than a few years. Especially not if we enter any sort of economic downturn/craziness from the very inconsistent and unpredictable decisions being made by the current administration
    - thewebguyd 1y ago
      You would think so. Investors are eventually going to want a return on their money put in. But there seems to be a ton of hype and irrationality around AI, even worse than blockchain back in the day. I think there's an element of FOMO - should someone actually get to AGI, or at least something good enough to actually impact the labor market and replace a lot of jobs, the investors of that company/product stand to make obscene amounts of money. So everyone pumps in, in hope of that far off future promise. But like you said, how long can this keep going before it starts looking like that future promise will not be fulfilled in this lifetime and investors start wanting a return.
deleted 1y ago
[deleted]
lordnacho 1y ago
Are you saying they'd be profitable if they didn't pour all the winnings into research? From where I'm standing, the models are useful as is. If Claude stopped improving today, I would still find use for it. Well worth 4 figures a year IMO.
- dvfjsdhgfv 1y ago
  For me, if Anthropic stopped now, and given access to all alternative models, they still would be worth exactly $240 which is the amount I'm paying now. I guess Anthropic and OpenAI can see the real demand by clearly seeing what are their free:basic:expensive plan ratios.
  - danielbln 1y ago
    You may want to pay for Claude Max outside of the Google or iOS ecosystem and save $40/month.
- apwell23 1y ago
  > Well worth 4 figures a year IMO only because software engineering pay hasn't adjusted down for the new reality . You don't know what its worth yet.
  - fkyoureadthedoc 1y ago
    Can you explain this in more detail? The idiot bottom rate contractors that come through my team on the regular have not been helped at all by LLMs. The competent people do get a productivity boost though. The only way I see compensation "adjusting" because of LLMs would need them to become significantly more competent and autonomous.
    - lelanthran 1y ago
      > Can you explain this in more detail? Not sure what GP meant specifically, but to me, if $200/m gets you a decent programmer, then $200/m is the new going rate for a programmer. Sure, now it's all fun and games as the market hasn't adjusted yet, but if it really is true that for $200/m you can 10x your revenue, it's still only going to be true until the market adjusts! > The competent people do get a productivity boost though. And they are not likely to remain competent if they are all doing 80% review, 15% prompting and 5% coding. If they keep the ratios at, for example, 25% review, 5% prompting and the rest coding, then sure, they'll remain productive. OTOH, the pipeline for juniors now seems to be irrevocably broken: the only way forward is to improve the LLM coding capabilities to the point that, when the current crop of knowledgeable people have retired, programmers are not required. Otherwise, when the current crop of coders who have the experience retires, there'll be no experience in the pipeline to take their place. If the new norm is "$200/m gets you a programmer", then that is exactly the labour rate for programming: $200/m. These were previously (at least) $5k/m jobs. They are now $200/m jobs.
dvfjsdhgfv 1y ago
> If they stopped today to focus on optimization of their current models to minimize operating cost and monetizing their user base you think they don't have a successful business model? Actually, I'd be very curious to know this. Because we already have a few relatively capable models that I can run on my MBP with 128 GB of RAM (and a few less capable models I can run much faster on my 5090). In order to break even they would have to minimize the operating costs (by throttling, maiming models etc.) and/or increase prices. This would be the reality check. But the cynic in me feels they prefer to avoid this reality check and use the tried and tested Uber model of permanent money influx with the "profitability is just around the corner" justification but at an even bigger scale.
- ghc 1y ago
  > In order to break even they would have to minimize the operating costs (by throttling, maiming models etc.) and/or increase prices. This would be the reality check. Is that true? Are they operating inference at a loss or are they incurring losses entirely on R&D? I guess we'll probably never know, but I wouldn't take as a given that inference is operating at a loss. I found this: https://semianalysis.com/2023/02/09/the-inference-cost-of-search-disruption/ https://semianalysis.com/2023/02/09/the-inference-cost-of-se... which estimates that it costs $250M/year to operate ChatGPT. If even remotely true $10B in revenue on $250M of COGS would be a great business.
  - dvfjsdhgfv 1y ago
    As you say, we will never know, but this article[0] claims: > The cost of the compute to train models alone ($3 billion) obliterates the entirety of its subscription revenue, and the compute from running models ($2 billion) takes the rest, and then some. It doesn’t just cost more to run OpenAI than it makes — it costs the company a billion dollars more than the entirety of its revenue to run the software it sells before any other costs. [0] https://www.lesswrong.com/posts/CCQsQnCMWhJcCFY9x/openai-lost-usd5-billion-in-2024-and-its-losses-are https://www.lesswrong.com/posts/CCQsQnCMWhJcCFY9x/openai-los...
    - 1y ago
dbalatero 1y ago
They might generate 10b ARR, but they lose a lot more than that. Their paid users are a fraction of the free riders. https://www.wheresyoured.at/openai-is-a-systemic-risk-to-the-tech-industry-2/ https://www.wheresyoured.at/openai-is-a-systemic-risk-to-the...
- Cthulhu_ 1y ago
  That's fixable, a gradual adjusting of the free tier will happen soon enough once they stop pumping money into it. Part of this is also a war of attrition though, who has the most money to keep a free tier the longest and attract the most people. Very familiar strategy for companies trying to gain market share.
  - sc68cal 1y ago
    That assumes that everyone is willing to pay for it. I don't think that's an assumption that will be true.
    - mike-cardwell 1y ago
      Those that aren't willing to pay for it directly, can still use it for free, but will just have to tolerate product placement.
    - ebiester 1y ago
      Consider the general research - in all, it doesn't eliminate people, but let's say it shakes out to speeding up developers 10% over all tasks. (That includes creating tickets, writing documentation, unblocking bugs, writing scripts, building proof of concepts, and more rote refactoring, but does not solve the harder problems or stop us from doing the hard work of software engineering that doesn't involve lines of code.) That means that it's worth up to 10% of a developer's salary as a tool. And more importantly, smaller teams go faster, so it might be worth that full 10%. Now, assume other domains end up similar - some less, some more. So, that's a large TAM.
    - LordDragonfang 1y ago
ehutch79 1y ago
Revenue is _NOT_ Profit
- throwawayoldie 1y ago
  And ARR is not revenue. It's "annualized recurring revenue": take one month's worth of revenue, multiply it by 12--and you get to pick which month makes the figures look most impressive.
  - UK-Al05 1y ago
    That's still not profit.
    - throwawayoldie 1y ago
      I know. It's a doubly-dubious figure.
  - jdiff 1y ago
    Astonishing that that concept survived getting laughed out of the room long enough to actually become established as a term and an acronym.
    - eddythompson80 1y ago
      It’s a KPI just like any KPI and it’s gamed. A lot of random financial metrics are like that. They were invented or coined as a short hand for something. Different investors use different ratios and numbers (ARR, P/E, EV/EBITDA, etc) as a quick initial smoke screen. They mean different things in different industries during different times of a business’ lifecycle. BUT they are supposed to help you get a starting point to reduce noise. Not as a the 1 metric you base your investing strategy on.
      - jdiff 1y ago
        I understand the importance of having data, and that any measurement can be gamed, but this one seems so tailored for tailoring that I struggle to understand how it was ever a good metric. Even being generous it seems like it'd be too noisy to even assist in informing a good decision. Don't the overwhelmingly vast majority of businesses see periodic ebbs and flows over the course of a year?
827a 1y ago
One thing we're seeing in the software engineering agent space right now is how many people are angry with Cursor [1], and now Claude Code [2] (just picked a couple examples; you can browse around these subreddits and see tons of complaints). What's happening here is pretty clear to me: Its a form of enshittification. These companies are struggling to find a price point that supports both broad market adoption ($20? $30?) and the intelligence/scale to deliver good results ($200? $300?). So, they're nerfing cheap plans, prioritizing expensive ones, and pissing off customers in the process. Cursor even had to apologize for it [3]. There's a broad sense in the LLM industry right now that if we can't get to "it" (AGI, etc) by the end of this decade, it won't happen during this "AI Summer". The reason for that is two-fold: Intelligence scaling is logarithmic w.r.t compute. We simply cannot scale compute quick enough. And, interest in funding to pay for that exponential compute need will dry up, and previous super-cycles tell us that will happen on the order of ~5 years. So here's my thesis: We have a deadline that even evangelists agree is a deadline. I would argue that we're further along in this supercycle than many people realize, because these companies have already reached the early enshitification phase for some niche use-cases (software development). We're also seeing Grok 4 Heavy release with a 50% price increase ($300/mo) yet offer single-digit percent improvement in capability. This is hallmark enshitification. Enshitification is the final, terminal phase of hyperscale technology companies. Companies remain in that phase potentially forever, but its not a phase where significant research, innovation, and optimization can happen; instead, it is a phase of extraction. AI hyperscalers genuinely speedran this cycle thanks to their incredible funding and costs; but they're now showcasing very early signals of enshitifications. (Google might actually escape this enshitification supercycle, to be clear, and that's why I'm so bullish on them and them alone. Their deep, multi-decade investment into TPUs, Cloud Infra, and high margin product deployments of AI might help them escape it). [1] https://www.reddit.com/r/cursor/comments/1m0i6o3/cursor_quality_is_getting_worse_every_day/ https://www.reddit.com/r/cursor/comments/1m0i6o3/cursor_qual... [2] https://www.reddit.com/r/ClaudeAI/comments/1lzuy0j/claude_code_has_gone_from_gamechanger_to_garbage/ https://www.reddit.com/r/ClaudeAI/comments/1lzuy0j/claude_co... [3] https://techcrunch.com/2025/07/07/cursor-apologizes-for-unclear-pricing-changes-that-upset-users/ https://techcrunch.com/2025/07/07/cursor-apologizes-for-uncl...
dkdbejwi383 1y ago
How many of those MAUs are crappy startups building a janky layer on top of the OpenAI API which will cease to exist in 2 years?
- reasonableklout 1y ago
  Last year, ChatGPT was 75% of OpenAI's revenue[1], not the API. [1]: https://www.businessofapps.com/data/chatgpt-statistics/ https://www.businessofapps.com/data/chatgpt-statistics/

airstrike 1y ago

No, because if they stop to focus on optimizing and minimizing operating costs, the next competitor over will leapfrog them with a better model in 6-12 months, making all those margin improvements an NPV negative endeavor.

bbor 1y ago

It’s just the natural counterpart to dogmatic inevitabilism — dogmatic denialism. One denies the present, the other the (recent) past. It’s honestly an understandable PoV though when you consider A) most people understand “AI” and “chatbot” to be synonyms, and B) the blockchain hype cycle(s) bred some deep cynicism about software innovation. Funny seeing that comment on this post in particular, tho. When OP says “I’m not sure it’s a world I want”, I really don’t think they’re thinking about corporate revenue opportunities… More like Rehoboam, if not Skynet.

dvfjsdhgfv 1y ago
> most people understand “AI” and “chatbot” to be synonyms This might be true (or not), but for sure not on this site.
- bbor 1y ago
  I mean... LLMs have not yet discovered a business model that justifies the massive expenditure of training and hosting them, The only way one could say such a thing is if they think chatbots are the only real application.

mc32 1y ago

Making money and operating at a loss contradict each other. Maybe someday they’ll make money —but not just yet. As many have said they’re hoping capturing market will position them nicely once things settle. Obviously we’re not there yet.

colinmorelli 1y ago
It is absolutely possible for the unit economics of a product to be profitable and for the parent company to be losing money. In fact, it's extremely common when the company is bullish on their own future and thus they invest heavily in marketing and R&D to continue their growth. This is what I understood GP to mean. Whether it's true for any of the mainstream LLM companies or not is anyone's guess, since their financials are either private or don't separate out LLM inference as a line item.

Forgeties79 1y ago

> that's because they are racing improve models. If they stopped today to focus on optimization of their current models to minimize operating cost and monetizing their user base you think they don't have a successful business model? I imagine they would’ve flicked that switch if they thought it would generate a profit, but as it is it seems like all AI companies are still happy to burn investor money trying to improve their models while I guess waiting for everyone else to stop first. I also imagine it’s hard to go to investors with “while all of our competitors are improving their models and either closing the gap or surpassing us, we’re just going to stabilize and see if people will pay for our current product.”

thewebguyd 1y ago
> I also imagine it’s hard to go to investors with “while all of our competitors are improving their models and either closing the gap or surpassing us, we’re just going to stabilize and see if people will pay for our current product.” Yeah, no one wants to be the first to stop improving models. As long as investor money keeps flowing in there's no reason to - just keep burning it and try to outlast your competitors, figure out the business model later. We'll only start to see heavy monetization once the money dries up, if it ever does.
- Forgeties79 1y ago
  Maybe I’m naïve/ignorant of how things are done in the VC world, but given the absolutely enormous amount of money flowing into so many AI startups right now, I can’t imagine that the gravy train is going to continue for more than a few years. Especially not if we enter any sort of economic downturn/craziness from the very inconsistent and unpredictable decisions being made by the current administration
  - thewebguyd 1y ago
    You would think so. Investors are eventually going to want a return on their money put in. But there seems to be a ton of hype and irrationality around AI, even worse than blockchain back in the day. I think there's an element of FOMO - should someone actually get to AGI, or at least something good enough to actually impact the labor market and replace a lot of jobs, the investors of that company/product stand to make obscene amounts of money. So everyone pumps in, in hope of that far off future promise. But like you said, how long can this keep going before it starts looking like that future promise will not be fulfilled in this lifetime and investors start wanting a return.

deleted 1y ago

[deleted]

lordnacho 1y ago

Are you saying they'd be profitable if they didn't pour all the winnings into research? From where I'm standing, the models are useful as is. If Claude stopped improving today, I would still find use for it. Well worth 4 figures a year IMO.

dvfjsdhgfv 1y ago
For me, if Anthropic stopped now, and given access to all alternative models, they still would be worth exactly $240 which is the amount I'm paying now. I guess Anthropic and OpenAI can see the real demand by clearly seeing what are their free:basic:expensive plan ratios.
- danielbln 1y ago
  You may want to pay for Claude Max outside of the Google or iOS ecosystem and save $40/month.
apwell23 1y ago
> Well worth 4 figures a year IMO only because software engineering pay hasn't adjusted down for the new reality . You don't know what its worth yet.
- fkyoureadthedoc 1y ago
  Can you explain this in more detail? The idiot bottom rate contractors that come through my team on the regular have not been helped at all by LLMs. The competent people do get a productivity boost though. The only way I see compensation "adjusting" because of LLMs would need them to become significantly more competent and autonomous.
  - lelanthran 1y ago
    > Can you explain this in more detail? Not sure what GP meant specifically, but to me, if $200/m gets you a decent programmer, then $200/m is the new going rate for a programmer. Sure, now it's all fun and games as the market hasn't adjusted yet, but if it really is true that for $200/m you can 10x your revenue, it's still only going to be true until the market adjusts! > The competent people do get a productivity boost though. And they are not likely to remain competent if they are all doing 80% review, 15% prompting and 5% coding. If they keep the ratios at, for example, 25% review, 5% prompting and the rest coding, then sure, they'll remain productive. OTOH, the pipeline for juniors now seems to be irrevocably broken: the only way forward is to improve the LLM coding capabilities to the point that, when the current crop of knowledgeable people have retired, programmers are not required. Otherwise, when the current crop of coders who have the experience retires, there'll be no experience in the pipeline to take their place. If the new norm is "$200/m gets you a programmer", then that is exactly the labour rate for programming: $200/m. These were previously (at least) $5k/m jobs. They are now $200/m jobs.

dvfjsdhgfv 1y ago

> If they stopped today to focus on optimization of their current models to minimize operating cost and monetizing their user base you think they don't have a successful business model? Actually, I'd be very curious to know this. Because we already have a few relatively capable models that I can run on my MBP with 128 GB of RAM (and a few less capable models I can run much faster on my 5090). In order to break even they would have to minimize the operating costs (by throttling, maiming models etc.) and/or increase prices. This would be the reality check. But the cynic in me feels they prefer to avoid this reality check and use the tried and tested Uber model of permanent money influx with the "profitability is just around the corner" justification but at an even bigger scale.

ghc 1y ago
> In order to break even they would have to minimize the operating costs (by throttling, maiming models etc.) and/or increase prices. This would be the reality check. Is that true? Are they operating inference at a loss or are they incurring losses entirely on R&D? I guess we'll probably never know, but I wouldn't take as a given that inference is operating at a loss. I found this: https://semianalysis.com/2023/02/09/the-inference-cost-of-search-disruption/ https://semianalysis.com/2023/02/09/the-inference-cost-of-se... which estimates that it costs $250M/year to operate ChatGPT. If even remotely true $10B in revenue on $250M of COGS would be a great business.
- dvfjsdhgfv 1y ago
  As you say, we will never know, but this article[0] claims: > The cost of the compute to train models alone ($3 billion) obliterates the entirety of its subscription revenue, and the compute from running models ($2 billion) takes the rest, and then some. It doesn’t just cost more to run OpenAI than it makes — it costs the company a billion dollars more than the entirety of its revenue to run the software it sells before any other costs. [0] https://www.lesswrong.com/posts/CCQsQnCMWhJcCFY9x/openai-lost-usd5-billion-in-2024-and-its-losses-are https://www.lesswrong.com/posts/CCQsQnCMWhJcCFY9x/openai-los...
  - 1y ago

dbalatero 1y ago

They might generate 10b ARR, but they lose a lot more than that. Their paid users are a fraction of the free riders. https://www.wheresyoured.at/openai-is-a-systemic-risk-to-the-tech-industry-2/ https://www.wheresyoured.at/openai-is-a-systemic-risk-to-the...

Cthulhu_ 1y ago
That's fixable, a gradual adjusting of the free tier will happen soon enough once they stop pumping money into it. Part of this is also a war of attrition though, who has the most money to keep a free tier the longest and attract the most people. Very familiar strategy for companies trying to gain market share.
- sc68cal 1y ago
  That assumes that everyone is willing to pay for it. I don't think that's an assumption that will be true.
  - mike-cardwell 1y ago
    Those that aren't willing to pay for it directly, can still use it for free, but will just have to tolerate product placement.
  - ebiester 1y ago
    Consider the general research - in all, it doesn't eliminate people, but let's say it shakes out to speeding up developers 10% over all tasks. (That includes creating tickets, writing documentation, unblocking bugs, writing scripts, building proof of concepts, and more rote refactoring, but does not solve the harder problems or stop us from doing the hard work of software engineering that doesn't involve lines of code.) That means that it's worth up to 10% of a developer's salary as a tool. And more importantly, smaller teams go faster, so it might be worth that full 10%. Now, assume other domains end up similar - some less, some more. So, that's a large TAM.
  - LordDragonfang 1y ago

ehutch79 1y ago

Revenue is _NOT_ Profit

throwawayoldie 1y ago
And ARR is not revenue. It's "annualized recurring revenue": take one month's worth of revenue, multiply it by 12--and you get to pick which month makes the figures look most impressive.
- UK-Al05 1y ago
  That's still not profit.
  - throwawayoldie 1y ago
    I know. It's a doubly-dubious figure.
- jdiff 1y ago
  Astonishing that that concept survived getting laughed out of the room long enough to actually become established as a term and an acronym.
  - eddythompson80 1y ago
    It’s a KPI just like any KPI and it’s gamed. A lot of random financial metrics are like that. They were invented or coined as a short hand for something. Different investors use different ratios and numbers (ARR, P/E, EV/EBITDA, etc) as a quick initial smoke screen. They mean different things in different industries during different times of a business’ lifecycle. BUT they are supposed to help you get a starting point to reduce noise. Not as a the 1 metric you base your investing strategy on.
    - jdiff 1y ago
      I understand the importance of having data, and that any measurement can be gamed, but this one seems so tailored for tailoring that I struggle to understand how it was ever a good metric. Even being generous it seems like it'd be too noisy to even assist in informing a good decision. Don't the overwhelmingly vast majority of businesses see periodic ebbs and flows over the course of a year?

827a 1y ago

One thing we're seeing in the software engineering agent space right now is how many people are angry with Cursor [1], and now Claude Code [2] (just picked a couple examples; you can browse around these subreddits and see tons of complaints). What's happening here is pretty clear to me: Its a form of enshittification. These companies are struggling to find a price point that supports both broad market adoption ($20? $30?) and the intelligence/scale to deliver good results ($200? $300?). So, they're nerfing cheap plans, prioritizing expensive ones, and pissing off customers in the process. Cursor even had to apologize for it [3]. There's a broad sense in the LLM industry right now that if we can't get to "it" (AGI, etc) by the end of this decade, it won't happen during this "AI Summer". The reason for that is two-fold: Intelligence scaling is logarithmic w.r.t compute. We simply cannot scale compute quick enough. And, interest in funding to pay for that exponential compute need will dry up, and previous super-cycles tell us that will happen on the order of ~5 years. So here's my thesis: We have a deadline that even evangelists agree is a deadline. I would argue that we're further along in this supercycle than many people realize, because these companies have already reached the early enshitification phase for some niche use-cases (software development). We're also seeing Grok 4 Heavy release with a 50% price increase ($300/mo) yet offer single-digit percent improvement in capability. This is hallmark enshitification. Enshitification is the final, terminal phase of hyperscale technology companies. Companies remain in that phase potentially forever, but its not a phase where significant research, innovation, and optimization can happen; instead, it is a phase of extraction. AI hyperscalers genuinely speedran this cycle thanks to their incredible funding and costs; but they're now showcasing very early signals of enshitifications. (Google might actually escape this enshitification supercycle, to be clear, and that's why I'm so bullish on them and them alone. Their deep, multi-decade investment into TPUs, Cloud Infra, and high margin product deployments of AI might help them escape it). [1] https://www.reddit.com/r/cursor/comments/1m0i6o3/cursor_quality_is_getting_worse_every_day/ https://www.reddit.com/r/cursor/comments/1m0i6o3/cursor_qual... [2] https://www.reddit.com/r/ClaudeAI/comments/1lzuy0j/claude_code_has_gone_from_gamechanger_to_garbage/ https://www.reddit.com/r/ClaudeAI/comments/1lzuy0j/claude_co... [3] https://techcrunch.com/2025/07/07/cursor-apologizes-for-unclear-pricing-changes-that-upset-users/ https://techcrunch.com/2025/07/07/cursor-apologizes-for-uncl...

dkdbejwi383 1y ago

How many of those MAUs are crappy startups building a janky layer on top of the OpenAI API which will cease to exist in 2 years?

reasonableklout 1y ago
Last year, ChatGPT was 75% of OpenAI's revenue[1], not the API. [1]: https://www.businessofapps.com/data/chatgpt-statistics/ https://www.businessofapps.com/data/chatgpt-statistics/