Everyone is actually underestimating stickiness. The near billion users OpenAI has is actually a real moat and might translate into decent chunk of revenue.
My wife, for example, uses ChatGPT on a daily basis, but has found no reason to try anything else. There are no network effects for sure, but people have hundreds and thousands on conversation on these apps that can't be easily moved elsewhere. Understandable that it would be hard to get majority of these free users to pay for anything, and hence, advertising seems a good bet. You couldn't have thought of a more contextual way of plugging in a paid product.
I think OpenAI has better chance to winning on the consumer side than everyone else. Of course, would that much up against hundreds of billions of dollars in capex remains to be seen.
So in summary OpenAI are basing their valuation of 285 billion on the moat of 'users won't be arsed to download a different app'???
Seems optimistic when there is very little intrinsic stickness due to learning the UI or network effects. Perhaps a little bit chat history - but not 285 billions worth.
Also completely ignoring the fact that most devices things will start to come with the same features directly built into the device/app - and the largest market will be as a commodity backend api that the eventually users won't know or care if it's a google or openai model.
As I see it, they need to be doing stuff nobody else can ( in either price or performance ), otherwise it's hard to justify the valuation.
You'd be surprised that most people don't find any pleasure in comparing and trying out different software. They're looking for something which works and ChatGPT is just an amazing product. People aren't going to look for something else unless it breaks for some reason.
Most people who have a vehicle aren't trying out different motor oils, or comparing every month if they should change model, etc.
> As I see it, they need to be doing stuff nobody else can ( in either price or performance ), otherwise it's hard to justify the valuation.
Do you have a car? What does it do that no other car does?
> the moat of 'users won't be arsed to download a different app'???
don't even need to download anything, just open your browser and go to google.com to use gemini
last week-end, I've seen a non-tech friend who previously used chatGPT on his phone, just go on google to ask stuff to the AI (they have no idea it's gemini and it doesn't matter)
if you are not looking for having some kind of relationship with an AI (from what I understand people use chatGPT for this use case), but just looking for an AI to search stuff, then in my opinion you can't beat google search + gemini summary all at once for free with a single prompt
I think you're right about stickyness up to a point.
Cultural defaults seem unchangeable but then suddenly everyone knows, that's everyone knows, that OpenAI is passé.
OpenAI has a real chance to blow their lead, ending up in a hellish no-man's land by trying to please everyone: Not cool enough for normies, not safe enough for business, not radical enough for techies. Pick a lane or perish.
Not owning their own infrastructure, and being propped up by financial / valuation tricks are more red flags.
Being a first mover doesn't guarantee getting to the golden goose, remember MySpace.
Literally every industry has examples of businesses that don't excel at anything and still do well enough to carry on. In fact, in most industries, it's actually hard to see any business that's clearly leading on any specific front because as soon as it becomes an obvious factor in gaining market share the competing businesses focus on that area as well.
> Everyone is actually underestimating stickiness.
I think you're underestimating how fickle consumers are, and how much their choices are based on fashion and emotion. A couple more of these, and OpenAI will find itself relegated to the kids' table with Grok and Perplexity. https://www.technologyreview.com/2025/08/15/1121900/gpt4o-gr...
Is she paying for it? That is the only question that matters in the end.
For myself, I use LLMs daily and I would even say a lot on some days and I _did_ pay the 20€/mo subscription for ChatGPT, but with the latest model I cannot justify that anymore.
4o was amazingly good even if it had some parasocial issues with some people, it actually did what I expect an LLM to do. Now the quality of the 5.whatever has gone drastically down. It no longer searches web for things it doesn't know, but instead guesses.
Even worse is the tone it uses; "Let's look at this calmly" and other repeated sentences are just off putting and make the conversation feel like the LLM thinks I am about to kill myself constantly and that is not what I want from my LLM.
>Is she paying for it? That is the only question that matters in the end.
Don't underestimate advertising. Noone pays for Facebook or Google search. Yet the ad business with a couple billion users seems profitable enough to fund frontier LLM research and inference infrastructure as a side-gig in these companies. Google only rushed out AI overview because they saw ChatGPT eating their market share in information retrieval and Zuck is literally panicking about the fact that users share more personal details with OpenAI than on his doomscrolling attention sinks.
not necessarily, if openai managed to monetize free users. Could be through advertising, or integrations with marketplaces on commission (e.g. order your next Hello Fresh through ChatGPT? Get recommended a hotel?)
They could succeed where Alexa failed. A free user can even bring in more than a paid user if you look at some platforms like spotify, where apparently there is a large chunk of free users generating more income through ads than if they would pay
Most potential customers wouldn't ever think in terms as "justifying" a €20 purchase when the product is great.
ChatGPT (and competitors) is an incredibly high value tool, and €20 per month is nothing for somebody who wants or needs it. It's just a matter of if they use it enough to start hitting the daily limits.
>no longer searches web for things it doesn't know, but instead guesses.
This could very well have been a cost-reduction effort to try and simulate what it was doing before.
Somebody must think training has already looked at the web enough, or there may be too much slop now that there was no contingency for.
Then you've got tighter guardrails to make it more palatable for a wider audience.
I guess different people would draw the line differently, but when it goes from being worth money to not worth it any more that could be an enshittification effect.
I hear the claim that people already have their conversation on ChatGPT and can't move them. I'm curious, what are these discussions like? I've never continued an old discussion, I just start a new one every time I have a question. If the discussion is long, I often start a new chat to get a blank slate. My experience is that the chat history just causes confusion.
So I'm curious to understand: What are the discussions like that people go back to and would lose if they moved to another platform?
In my experience non-technical folks quite dig the memory feature. For me that's kinda context poisoning as a service, but I know people that get value out of it (or at least strongly feel they do). Not sure how one would migrate that.
I'm curious from the other direction, what are the conversations like if you feel they are easy to move?
Do you have the memory feature disabled? I have the feeling this in particular is doing absolutely loads behind the scene, e.g summarising all conversations and adding additional hidden context to every request.
I can start a new chat in the UI right now, ask it what my job is, what my current project is, how many kids I have, what car I drive etc. It'll know the answer already.
I think it's this conversation history - or maybe better yet if we think of it as this "relationship" - that people are saying is going to make it hard to move.
Regardless of whether there is value in chat history or not, for some people it is important.
Back in the day during the music streaming wars there were tons of "move your playlists from A to B" services. Streaming services could not hold on to customers because all their playlists were on there.
I'm sure that similar services will pop up for chatbots.
Also, you can always just ask your chatbot to generate a file with your chat history, given that it's all part of the context anyway.
yeah the 'sessions' approach is probably going to be deprecated. one continuous chat is where it's at , perhaps with some bookmarks on the side for easy access
or perhaps a thread-based chat like reddit or HN, where you can branch off an older conversation with yourself
"Near billion users", yet less than 5% pay them a single penny[1]. Like you said, the vast majority of these will never pay anything, but I'd argue the majority will migrate to the "next" free provider as soon as OpenAI starts inserting too many ads into the product.
I watched my partner switch from OAI to DeepSeek during the last outage and she hasn't been back to OAI since. I am skeptical there is any actual stickyness when basically all of the chatbots do the same thing for the casual user.
Google Search has no stickiness and they managed to build a behemoth.
ChatGPT is a great product, but the lack of stickiness comes into play because there are many viable alternatives.
They’re all going to have to monetise the consumer segment at some stage, and I think that’s likely to be via ads on a freemium tier in most instances.
Anecdata point: I canceled my ChatGPT pro subscription last year over some shitty thing Altman did at OpenAI and easily moved over to Claude. The only thing I took with me was the system prompt or whatever it's called, I couldn't care less about my conversation history. I'm planning to do the same thing with my Claude subscription if Anthropic kowtows to the Pentagon. These services are not sticky at all IMO.
Anthropic already decided to do business with the "killing people" department of the government. I think the battle was lost there, rather than whether or not they cross a line in the sand they drew to act as if they're the ethical AI company despite making products that are used to kill people. I'm sure the result of this battle will be some compromise that allows the Pentagon to get whatever they want while offering a fig leaf to Anthropic to continue their ethicality show.
Anthropic donated $20 million to Public First Action[1], a PAC that promotes Republican Senator Marsha Blackburn and her sponsored Kids Online Safety Act (KOSA)[2], a bill that will force everyone to scan their faces and IDs to use the internet under the guise of saving the children.
The legislative angle taken by companies like Anthropic is that they will provide the censorship gatekeeping infrastructure to scan all user-generated content that gets posted online for "appropriateness", guaranteeing AI providers a constant firehose of novel content they can train on and get paid for the free training. AI companies will also get paid to train on videos of everyone's faces and IDs.
As for why Blackburn supports KOSA[3]:
> Asked what conservatives’ top priorities should be right now, Senator Blackburn answered, “protecting minor children from the transgender [sic] in this culture and that influence.” She then talked about how KOSA could address this problem, and named social media platforms as places “where children are being indoctrinated.”
If Anthropic, the PACs it supports and Blackburn get their way with KOSA, the end result will be that anything posted on the internet will be able to be traced back to you. Web platforms will finally be able to sell their userbases as identifiable and monetizable humans to their partners/advertisers/governments/facial recognition systems/etc. AI companies will legally enshrine themselves as the official gatekeepers and censors of the internet, and they will be paid to train on the totality of novel human creativity in real-time.
> but people have hundreds and thousands on conversation on these apps that can't be easily moved elsewhere.
Except these aren't conversations in the traditional sense. Yes, there's the history of prompts and responses exchanged. But the threads don't build on each other - there's no cross-conversational memory, such as you'd have in a human relationship. Even within a conversation it's mostly stateless, sending the full context history each time as input.
So there's no real data or network effect moat - the moat is all in model quality (which is an extremely competitive race) and harness quality (same). I just don't think there's any real switching cost here.
I use OpenAI a lot on the paid plan via the UI. It now knows absolutely loads about me and seems to have a massive amount of cross conversational memory. It's really getting very close to what you'd expect from a human conversation in this regard.
Sure the model itself is still stateless, and if you use the API then what you say is true.
But they are doing so much unseen summarisation and longer context building behind the scenes in the webapp, what you see in the current conversation history is just a fraction of what is getting sent to the model.
I see people who have conversations spanning months. They don't start new threads and instead go back to existing threads to continue the topic. They also reference the prior threads discussion many times.
This would feel like a switching cost for people who use the system that way.
> Everyone is actually underestimating stickiness. The near billion users OpenAI has is actually a real moat and might translate into decent chunk of revenue.
I’ve got a small-ish sample of friends who are regular people and use various AI chatbots because mobile phone providers now commonly bundle an AI subscription with their services. People seem to switch between Perplexity, Claude, and ChatGPT without any trouble. It does not look sticky at all to me and the half-a-percent difference in benchmarks we love to obsess about does not translate at all in increased user satisfaction.
I don't think chat history is enough for real stickiness.
But the trillion dollar question is, what is? Now that I think about it, I'd bet heavily on Google. They've got your email, your photos, your location history, yada yada. Once they're able to pull all that into AI and make a reasonably cohesive product out of it, it seems like that's what people would use by default. Plus they've got a browser, search page, and phone OS that all can lead you to their AI.
They could train custom LoRA layers to mimic your tone, encode special tokens that indicate your name and data and various facts about you and your contacts, to make output more accurate, consistent, and personalized. Lots of possibilities for increased stickiness.
Even enterprise-wise, gemini is pretty good at coding and if your company has all its docs on Google docs, that could become a pretty seamless integration. They can even build their agents to prefer GCP, or maybe make that the free tier but have other providers support be more expensive.
At some point, a reasonable business model might be "we replace your engineering team with AI plus a few Google engineers on retainer for when things get wonky," which could scale to pretty large. (Granted this sounds more like a msft power move.)
They already have all the infrastructure, all they need is a reasonable competitor to github. They really screwed up losing out to msft on that one!
Idk, habit and the devil you know are powerful as hell. Google has enshittified search nearly beyond imagination, but it's still where the vastly overwhelming majority of people search.
In theory you can export your data from ChatGPT under Settings > Data Controls. In practice, I tried this recently and the download link was broken. Convenient bug I must say.
My wife, for example, uses [Netscape Navigator] on a daily basis, but has found no reason to try anything else. There are no network effects for sure, but people have hundreds and thousands on [bookmarks] on these apps that can't be easily moved elsewhere.
ChatGPT has a good name. It's weird and awkward but it still rolls off the tongue. And I am saying that as a non native English speaker because the name has been migrated to other languages with the English pronunciation.
In comparison, Claude's name is very bad, it just doesn't sound right and people might mishear me when I say it. I never say "Claude" when talking to other, especially non-technical people, and instead say "ChatGPT" even though I am using Claude exclusively.
Google has another problem - they advertise their models as separate products. There is Gemini and there is Nano Banana, also Nano Banana Pro. But they are all somehow under the same product which is still called Gemini. I understand the distinction but I am sure many non-technical people find it confusing.
Claude may seem incongruous compared to the others, however it's the only human sounding name, compared to the robotic "chatgpt" or others that sound generic or bland company names (Gemini, perplexity).
They intentionally chose a more bland sounding name, as, I assume, they wanted to emphasise the "safe" nature compared to their competitors.
As more information comes out about openai, people may choose to move to for other reasons, such as
- Openai adding ads
- Openai's president donating millions to a MAGA PAC
- Openai getting closer to the US military whilst anthropic standing their ground and rejecting them.
- Openai's recent products not being at the top of the benchmarks
They initially wanted to call it just "Gemini 2.5 Flash Image (preview)" but the Internet stuck with the anonymous codename Nano-banana from LMArena because it's interesting and quirky. Google didn't officially adopt it until several days after the public release, exactly because of what you say. Eventually, not using it in their comms got more confusing because regular people were asking how they can find this Nano banana thing everyone is hyped about.
I don't know but around here common people all say "Chatty" nowadays, and also most people if writing the correct name fail to spell "gpt" right quite often in chat.
I believe specifically for Microsoft, they did bundle a default replacement for chatGPT in a lot of different places (Bing chat, Copilot) which use OpenAI models! But the end product is notably worse than native interface. There is a bare-minimum-level of usability required.
For chat apps, good enough is good enough. For something as universally useful and easy to use as ChatGPT, the bar is higher. I don't want to comment on the financial feasibility, but whatever Microsoft put out has been a complete flop even when free, making ChatGPT $8 subscription seem worth it in comparison
I don’t know how much of an anecdote it is, but all the non-tech people with whom I talk about IA only know chatGPT. Competition is either non existent or the same thing. Among those, no one wants to pay the service, they just stop using it when limits are reached. I can’t say which users can turn the market around but chatGPT is indeed burned in the mind of many and because they don’t care about tech and are not interested in tech they won’t search for any other service it seems. Even after many discussions they don’t remember the names of other IA I told them
I would bet 100% of those people have either Apple or Android phone in their pocket. Android users already have easy access to Gemini, and Apple's Siri is going LLM soon enough as well.
Google and Apple just need to push their AI assistants hard enough, and most of the moat OpenAI has will be gone.
I commute on the train, I see students studying with it. I go for brunch on the weekend, I see parents consulting it while at the table with their infants. I'm at work, colleagues are using it all day. I leave work and I overhear the random woman smoking in the alleyway talking on her cellphone saying "so I asked chatgpt". It's mind-bogglingly pervasive, the last time something had such a seizmic cultural impact like this was I dunno, Facebook? And secondly, it's all one specific brand. I'm not encountering co-pilot or gemini in the meat-space.
Chatgpt is like "Jeep". My grandmother calls every suv a jeep. But they're not all jeeps. AI looks like chatgpt, but people are driving all sorts of different AIs.
I would guess OAI has no moat or stickiness beyond what governments and private companies will do to keep it afloat through equity and circular financing. Good enough AI is all most need, and they need it at the cheapest cost basis possible with the most convenient access.
Google will probably win on most of these fronts unless a coalition is formed to actively fight google at the business/government level. But, absent that, it will win out over oai and oai will probably bleed to death trying to become profitable.. whenever that happens. You'll likely see their talent and corresponding salaries shrink massively along this journey.
How many of those people are paying? I think many say “use ChatGPT” to mean any LLM. As you noted it seems you just see ChatGPT in the wild but that is anecdotal. It is certainly pervasive right now. But I know a lot of people currently switching to Gemini.
I personally prefer claude models for all my work. If I were them I would be very worried. They are never giving us AGI and I am skeptical they are worth .5 trillion. Their cash burn is insane. Once ads and price hikes come, people will migrate to companies that can still afford to subsidize (like Google).
Plus I heard they lowered projections recently? Sam honestly comes off as a grifter.
I think that's false. The cost of switching is so low that the best product will win and there's no moat.
I honestly can't see how OpenAI can possibly recoup the hundreds of billions poured into it at this point. I'd say AI assistants are no more sticky than browsers or search engines.
You might be tempted to say that Chrome or Google are sticky. But they're really not. A lot of people aren't old enough to remember the 90s when we had multiple search engines and people did switch. I know this goes against prevailing HN dogma but I'm sorry: Google is simply the best search engine. It doesn't have a magical hold on people. People aren't fooling themselves.
And Chrome? Before smartphones it was simply the better browser. Firefox used to have a much larger market share and Chrome ate their lunch. By being a better browser. Chrome was I think the first browser, or at least the first major browser, to do one process per tab. I still remember Firefox hanging my entire browser when something went wrong. I switched to Chrome in version 2 for that reason.
And now browsers are more sticky because of Chrome on Android and Safari on iOS. Safari really needs to be cross-platform, like seriously so. I know they briefly tried on Windows but they didn't really mean it.
Anyway, back to the point. I believe there's a certain amount of brand inertia but that's it. If Gemini dominates ChatGPT performance and UI/UX, people will switch so fast.
Google, Microsoft and Meta can survive the AI collapse. Apple is irrelevant (at least for now). OpenAI? Doomed IMHO.
> people have hundreds and thousands on conversation on these apps that can't be easily moved elsewhere.
I just asked it to build me a searchable indexed downloaded version of all my conversations. One shot, one html page, everything exported (json files).
I’m sure I could ask Claude to import it. I don’t see the moat.
I think that kind of inertia mostly lasts as long as there is no financial incentive to move. A ChatGPT user who is not paying anything to OpenAI is of little benefit to them, and has little incentive to switch. However if OpenAI start trying to make money off those users by adding advertising, or removing the free tier, then things may change. Google can afford to subsidize chat from their other revenue streams, but OpenAI can't.
>However if OpenAI start trying to make money off those users by adding advertising, or removing the free tier, then things may change.
Tech forums tend to be in a bit of a bubble. People said the same thing about Netflix and it just quickly became their most popular sub. People don't care about advertising unless it's really obnoxious.
The idea that people will unsub en masse once Open AI starts rolling ads is a pipe dream. And the kind of user that won't pay and won't suffer some ads is the kind of user nobody wants.
I've actually been using the Gemini app more because it auto-deletes old history. I like using LLMs without thinking this is going to stick around forever.
Models are relatively interchangeable for day-to-day use anyway.
OpenAI is already building complex user models. And I mean, super detailed user models - where you are from, what you do, what are your most vulnerable weaknesses, what you care about the most and everything else. This is information even the world's largest advertising company would struggle to put together across their fragmented eco-system (Gmail, Search, etc), but OpenAI has all this on a silver platter. And that scares me, because, a lot of people use ChatGPT as a therapist. We know this because of their advertising intent which they've explicitly expressed. Advertising requires good user models to work (so advertisers can efficiently target their audience) and it is the only way to prove ROI to the advertisers. "But, OpenAI said they won't do targeted ads..". Remember, Google said "Don't be evil" once upon a time too..
That's ok, we use ChatGPT only for coding. We should be good, right? Umm, no. They already explicitly expressed the intention to take a percentage of your revenue if you shipped something with ChatGPT, so even the tech guys aren't safe.
"As intelligence moves into scientific research, drug discovery, energy systems, and financial modeling, new economic models will emerge. Licensing, IP-based agreements, and outcome-based pricing will share in the value created. That is how the internet evolved. Intelligence will follow the same path."
So yes, OpenAI has the best chance to win on the consumer side than anyone else. But, that's not necessarily a good thing (and the OpenAI fanboys will hate me for pointing this out).
> They already explicitly expressed the intention to take a percentage of your revenue if you shipped something with ChatGPT, so even the tech guys aren't safe.
Wasn't there already a ruling that LLM output is not protected by copyright?
I think defaultism plays a huge role. If your wife's next smartphone or TV or whatever comes with AI made by a different company, I think she won't really care and use that if it's good.
By the way this is a perfectly rational stance. If the supermarket next to me stopped stocking Coca Cola, I would just by Pepsi.
The moment openai starts charging for their service properly, people will start shopping around.
See power users such as devs with coding assistants that have model selection dropdowns allowing you to switch on a whim. There is zero loyalty or stickiness in the paying user crowd.
I am starting to believe that OAI might actually succeed at getting per token inference cost to where it needs to be. Or that it's already there in principle.
Wafer scale compute is a very big deal. Most of HN is probably still unaware that you can get tokens out of one of these devices right now via public API offerings.
Not sure how that works when there are fierce competitions, and openai's product is not substantially better than the rest. There are US competitors, then China.
Take ozempic as an example. The word is already part of the culture, but the company is losing badly to lly. Novo nordisk is projecting revenue DECLINE while eli lilly is still growing massively. I am not even sure people know other glp1 drugs other than ozempic. I don't even remember lilly drugs name.
I think people should not underestimate the market. It's a dynamic game where engineering intuition might not be enough
Google is sticky too, and has a huge moat around that access (android, browsers).
Google hasn't yet pushed hard into dominating the chatGPT use case, but they could EASILY push out chatGPT if they tried. For example, if they instantly turned their search page to the gemini chat, they would instantly have dominated openAI use cases. I'm not saying they would do that, they will probably go for the 'everything app' approach slowly
I think the use cases of chatGPT and google are not differentiated enough to justify 2 winners
Netscape had a 90% market share in 1995. If OpenAI is metaphorically netscape, what prevents its competitors from prying away customers every day? What prevents google/facebook/microsoft from using their position to bundle chat experiences? Especially if the tech is a commodity and OpenAI's models are about as good as everyone elses?
In 1995 no one used the web still. Sure, we all did, but it was pretty niche. I think you could argue that chatbots are niche as well, but the user base of OpenAI is way larger now than Netscape in 1995. Netscape had probably 25 million users at the end of 1995. ChatGPT has about 800 million.
I never considered that. When I change LLM models its usually due to two reasons.
1. the current AI model is producing answers that do not met my needs so I try multiple others at the same time and the one that produces the best answer I stick with until I have this problem again.
2. there is a new model released and advertises a new capability that I want to try out.
I can imagine that for many people the answer that ChatGPT generates is adequate enough that they never need to try another model even if better answers exists from another model. For people with less complex needs this is a very real stickiness. Why make the effort to try something new if the answer is adequate.
In this case, OpenAI would only f*k up if they change the pricing significantly, add intrusive ads or their answers become significantly worse.
They're losing market share and the growth of active user plateaued. They captured all the normies who learned about llms on TV but these people will never spend a cent as you said.
I’m not rooting for open AI but OpenRouter is a very self selecting group. Most API users of Anthropocic or OpenAi would just go through the normal API
I'm surprised how many of my technical team use free ChatGPT in their personal lives. The rest have Claude subscriptions. I'm the only one with ChatGPT and Claude subs and I'll be switching from Claude Pro to Ckaude Max and cancelling ChatGPT, since I only use it when I hit my Claude quota.
Switching llms is like switching a car. Its a bit annoying in the beginning, it responds slightly different and you need to change you subconscious habits before it feels comfortable. Why everyone always complains about new models. So unless there is a very obvious improvement; most users will prefer to stick to their current llm
That has not been my experience at all. My mom and dad were able to switch from ChatGPT to Gemini without any friction whatsoever. I myself round robin between Claude, Gemini and ChatGPT all the time.
I disagree. Are people really that attached to their conversations though?
Anecdotally, the vast majority of my own conversations and coding interactions are transient in nature, to the point where I prefer to use the ‘temporary’ mode in whatever tool I’m using.
For coding, every project needs a plan and readme to get whatever agent back up to speed with what the task is. Anyone with a paid-for GH Copilot license knows that you can just switch between whatever provider at a whim, depending on the needs of your task or financial requirements.
I think people will find it easier to revert back to Siri 2.0 if that ever materialises, in which case the stickiness moat is bridged by a more familiar and widely integrated abstraction layer.
I imagine the stickiest customers would be large enterprises. You aren't going to get the evangelists to stick on a single model provider, so their best bet is probably employees who are going to have their choices dictated to them by whoever purchases the softare. (Especially in large enterprises where using an unapproved AI provider is likely not allowed, or the AI is imposed on the workers.) The question then is, how do you differentiate yourself in enterprise sales? As much as people seem to dislike Copilot, from a business standpoint "buy the extra microsoft thing in our current contract" or "buy the extra google thing in our current contract" could likely be a lot cheaper/less friction.
It's really easy to overcome that -- just sponsor some IndieDevs to flood the internet with scripts and tools to migrate all your conversations from OpenAI. Make it easy for people to switch using a simple process, make sure it's well distributed, and BOOM! Watch their user count drop like a rock. People act like just because a service has a lot of users it can't be destroyed. Anyone who has ever worked at a large web company can tell you otherwise. These things can be destroyed in a just a few days if they are targeted.
They look like fortresses from the outside, but they are all incredibly vulnerable. That's the truth they don't want people to know or realize just how vulnerable they all are.
I might have sessions I revisit over a few weeks, but nothing longer than that. The conversations feel as ephemeral as the code produced. Some tiny fractions of it might persist long term, but most of it is already forgotten and replaced by lunch time.
I disagree. So far I've seen people use "Photoshop" and "Google" as verbs. No one uses "ChatGPT" as a verb. People do use ChatGPT but the brand recognition isn't that strong.
My anecdotes are that Google is winning even on consumer side.
As a verb, no, but the product name somehow feels the wrong shape to verb it. I'd say the voice assistants have Google at a disadvantage for similar reasons: "OK Google" is clunky, whereas "Hey Siri," and "Alexa," are not.
But to ChatGPT: when I wander around Berlin, I do overhear people talking about ChatGPT by name.
For all the typical integrated LLM-based "assistants" in other products, I mainly hear people saying things like "I hate it" and "how do I turn this off" and so on, including the one Google has on its search results.
The other pure-play chat-bots that have enough mind-share to even be in the news are Grok (where twitter users seem to like it a lot, even though everyone else up to and including non-US world governments hate it to the point of wanting it banned), Claude (but even then only because of Claude Code), and DeepSeek (because it shows China has no difficulty keeping up with the US). I heard about Mistrial when it was new, but even with the app on my phone I didn't think about it again until about a month ago.
Ask a normal person about Gemini, I'd expect them to think you were talking astrology, not AI.
In my experience, they do, a lot. "I asked ChatGPT" is something I hear a lot. And yes, this example is not using ChatGPT as a verb, but the idea of brand recognition is there; it's just a grammar thing.
How do you jump to Gemini from AIO? (I know there's AI mode, but it's separate from the Gemini chat product afaik -- except maybe sharing some model lineage)
I don't know. I switched to Gemini and haven't missed anything from OpenAI even for a second. I could switch back to OpenAI and not miss anything from Gemini. I don't feel the stickiness AT ALL.
I don't think they have a billion active users who opted-in. Google/Apple/Microsoft are the gatekeepers (for the most part) for retail users and they decide who is on by default. The USG isn't going to step-in and the EU won't step in either.
So I suspect that Google will lean into Gemini, Microsoft will lean into OpenAI, and Apple ... it's a tough question what they do in the longer term.
For business users it's a different story and I see room for Anthropic to shine. And then there are the specialty AI services but those are all different markets from the general purpose AI.
I think Google may just end up winning on the good enough / cheap enough dimensions as things get more commoditized in LLM world.. in that they can be the lower cost provider given how vertically integrated they would be compared to OpenAI relying on hyperscalers.
Just as people underestimate bundling and multiple-product companies. As soon as LLM corpos will start increasing prices to actually match expenses and recouping their immense debts customers will very quickly catch up how OAI product is x5 times more expensive than Google's and the only moat is is to open pre-installed Gemini :) .
Competing in freeware products is impossible as soon as monopoly emerges. Competing in paid products is way easier, especially after free money age has ended.
At this moment, I agree. Your average person (which doesn't really exist) has already been exposed and trained on ChatGPT. Arguing moving to another "chat" experience has not gone well, for example Bing, etc. Pretty sure Google had the "box" figured out first and won. I think people overthink how much effort people are willing to put into "change". There is nothing wrong with staying put if it works, after all, there is an unlimited number of other things happening in this world besides AI.
I definitely think they’ve nailed the personality better than others too. Gemini and grok are always paragraphs and paragraphs of text to sift through for something that with openai is usually digested to much less
The difficulty is that “winning” in this case is setting up a monopoly or duopoly and slowly increasing prices. It’s not clear if OpenAI can get so far ahead of the competition that it becomes a two or one horse race. Right now Anthropic and Google are at least as good. And the open source models keep them all honest pricing wise.
OpenAI will likely keep their billion users, and likely monetise them fairly effectively with ads. Their revenue will be considerable. It’s less clear that OpenAI will “win” and their competitors won’t.
My nontechnical friends only know about ChatGPT, all other LLMs are a complete and total mystery to them outside of what is built into Google's search engine and Copilot. I imagine they represent the majority of consumers. It'd require significant marketing campaign for most of them to switch or for OpenAI to make a substantial mistake.
do they use facebook or instagram? meta jammed their LLM into the search box there. Do they use google at all? the AI summary produced by Gemini leads you to click on "more details" with gemini.
so while this is technically true:
> My nontechnical friends only know about ChatGPT
they may actually use a ton of other LLMs without knowing
Most people I know with android phones, myself included, just use Gemini which is bundled with the OS and has a dedicated button, has excellent data and integration with maps and such.
When it comes to enterprise, non IT companies (banking, insurance, etc) in Europe seem to be defaulting to Google's offerings, Gemini and NotebookLM in particular.
The problem with the stickiness is that they will eventually need to start charging, and that friction point will immediately make them come undone. Let’s says they charge $1.99 a month, and Anthropic then step in with a six month free offer, and suddenly everyone has two apps on their phone they’re comfortable with, and it’s a price war over very lightly differentiated products
The problem is that, at least for now, it is dead easy to switch to something else. No need to convert anything, reconfigure anything, it is not like changing gmail to something else or dropping Word for LibreOffice.
Chat window is a chat window.
I can imagine that sooner or later things like OpenClaw (or its alikes) will become more popular and that could be something that will catch users.
It would take me minutes to copy across a histories of projects and continue relatively unscathed by the experience.
I use chatGPT and currently relatively like it. But there is no moat beyond that.
Not like, for example, whatssap where it's almost impossible to detach from it due to the network ... (I've really tried with about a 10% success rate)
But the (royal) Wife needs to 1) know that exporting is a concept, 2) automating an export is possible, 3) you could ask claude to do it, 4) what an API key is or how to connect services.
My mum, and probably nearly a billion other users, could probably imagine step 1 but not connect to step 2 beyond copy-paste. Most people are still out here sending screen shots of their phones instead of just copying a link or hitting "share" on the image.
But also a billion users is ChatGPT's biggest weakness. So many free users burning compute up. So many incentives to nerf the intelligence to affordable levels. Sounds like a nightmare.
several of my friends named their chatgpt 'Amanda' or 'George' because they talked about real mental issues with it. I don't see them moving to another platform because that's essentially asking them to leave their 'best friend/therapist'.
These articles are largely based on a false equivalence of LLM=moat.
That's not the case. OpenAI is advancing on many fronts; codex, vectorStore, embeddings, response API, containers, batch processing, voice-to-speech, image generation... the list goes on.
I wish it would be, but it's not. Gemini feels more sluggish, it's relatively overloaded with animations compared to chatgpt. Like most Google products.
As a counter anecdote, my wife stopped using it because it is quite terrible when you ask it about current events. She almost exclusively uses the Grok app now because it has the "best" internet search and current events results
Exactly. ChatGPT is ubiquitous for the new generation of AI (LLMs) for everyone outside our of bubble. I've spoken to dozens of friends and non-techncial folks about this topic over the last year and not a single one has ever said they use Gemini, Grok or Claude.
OpenAI has by far the strongest brand and user base. It's not even close.
And, when it comes to the product they've been locked in the last few months it seems. The coding models are no longer behind Anthropic's and their general-use chat offering has always been up there at the top.
I think you're overestimating stickiness. People spoke endlessly about stickiness of Google for years and years and it took what 18 months for Google search to become virtually irrelevant after LLMs came along?
They are more easily moved than other data honestly. You can use chat gpt to build your own chatbot and then export all of your data from openai and load it into the new chatbot.
Completely disagree with this take. I was an early free OpenAI user and switched to Gemini once it got good enough and bundled a bunch of services together to make the paid product free. OpenAI will need distribution to maintain any kind of durable market share. They need to become a bundler of other subs, or else they will just be the next Disney+ or Spotify that needs telecoms (Hah!) to push their paid product onto user's phone bills.
> Everyone is actually underestimating stickiness. The near billion users OpenAI has is actually a real moat and might translate into decent chunk of revenue.
Maybe you're overestimating their "moat" and stickiness. The dust is still settling on this madness and "OpenAI"[1] creates a lot of noise in the market.
These LLMs are being rapidly commoditized, very soon they will become as "boring" as virtual machines or containers. Altman has the exceptional skill to dupe people into giving their money to him. The "infinite money glitch" that he has been exploiting isn't really infinite.
I just hope there'll be a breakthrough with truly transparent LLMs that will stabilize this madness. As I've griped[2] two years ago, I find OpenAI too scummy, and it is unlikely that they will "win" with their sleazy ways.
[1] Air quotes because of their persistent abuse of the word "open"
nah, open ai doesn't have a moat it has a brief window to get a lot cheaper to run or it's going to go pop when someone figure out how to do inference a lot cheaper.
This is the real question. Is she willing to pay $20 per month when Google's Gemini is free? Google can remain irrational longer than OAI can remain solvent.
I really like your analysis and agree up to a point.
The problem with a moat in the consumer space is it depends on brand and marketing. OpenAI came into this world as a tech novelty, then an amazing tech tool, then a household name.
But… can they compete with massive consumer companies like Apple, Google, etc? In the long run?
There’s no technical reason they can’t. The question is whether they have consumer marketing in their blood. The space doesn’t have a lot of network effects, so it’s not like early Facebook where you had to be on it because everyone was.
Not saying they’ll fail, just saying it would be a significant challenge to be a hybrid frontier model / consumer product company.
The tech landscape is littered with companies they had users who couldn’t monetize through ads. Beside the costs of serving request via LLMs is orders of magnitude greater than a search result.
On top of that, OpenAI is a sharecropper on other companies’ server, they depend on another company’s search engine and unlike Google, they are dependent on Nvidia.
Don’t forget that most browsing is done on the web and Google is the default search engine on almost every phone sold outside of China.
Microsoft is surviving precisely because of stickiness as you put it. But their users have to use them, and have to pay for it. There are very few people that use openai today that have to pay for it, those forced to use it are typically doing so via free avenues like windows copilot.
OpenAI has the stickiness of MSN news or MS Teams. Your wife uses chatgpt on a daily basis but is she paying for it? If they charge her $0.99/mo will she not look at alternatives? If she gets two or three bad responses from chatgpt in a row, will she not explore alternatives to see if there is something better? Does she not use google? If she does, she is already interacting with gemini everyday via their AI overview.
OpenAI has a first-to-market advantage, not a moat as you think. they can absolutley dominate the market, if they stay on top of their game. Ebay was the main online shopping network, they had that advantage, they were even the ones that made Paypal a thing! But they're relatively little used now, better alternatives crushed them.
Amazon was the first-to-market with cloud services, they didn't get worse in any significant way, but their market share is not as great as it used to be, Azure has gained decent ground on them. 10 years ago the market share break down was 31/7/4, now it is 28/21/14 for AWS/Azure/GCP respectively.
For OpenAI to survive it needs most of the market share, if it gets only a 3rd for example, the AI industry on its own needs to be a $1T+ industry. Over the past 10 years revenue alone (not profit) for AWS has been $620B total and just made $128B in revenue (highest) last year. OpenAI needs to make in profits (not revenue) what AWS made last year in revenue by 2029 just to break even. If it manages to just break even by then, it needs to have more profits than the revenue AWS managed to attain after its entire lifetime until now. It's far easier to switch LLM models than cloud providers too!
Their only remote way of survival, I hate to say it, is by going the way of palantir and doing dirty things for governments and militaries. they need a cash-cow client that can't get anyone else like that. And even then, being US-based, I don't think outside the US any military is insane enough to use OpenAI at all due to geopolitics. Even in sectors like education, Google (via chromebooks) is more likely to form dependence than Microsoft via OpenAI since somehow they're more open to arbitrary apps due to historical anti-trust suits.
I can see a somewhat far-fetched argument being made for their survival, but only on thin-threads and excellent execution. But I can't see how they can actually survive competition. They're using the Azure strategy for market share, they're banking on AI being so ubiquitous that existing vendor-lock-in mindset will serve as a moat. They'll need to be much more profitable than AWS in like 1/5th of the time. Their product is comparable to (and literally is in Azure) one of many cloud service offerings, as oppose to an entire cloud provider, and their costs are huge similar to cloud providers like needing their own data-centers level huge, they need to overcome those costs, and on top of that have $125B> revenue in like 2 years!!
I have started using chatgpt for everything from financial planning to holiday planning to product purchase. Whenever I think I hit something useful I add it to memory. I'm a "go" plan user because they had a promotional offer that gave me free access to the plan for a year. Will I continue after one year? Truth is nothing I have in chatgpt cannot be recreated elsewhere. But if I care about keeping those memories I might. I think the real challenge for me now is finding back out conversations, it seems their history search is quite bad.
Yup this is just another case of the HN bubble. I polled a bunch of non technical friends recently who I know use AI on a daily basis. Out of 10+ maybe 2 had ever heard of Claude, and no one had any interest in trying it.
ChapGPT has become the AI verb, and in the consumer space it is not getting dethroned.
Gemini is the only real competitor to OpenAI in the consumer space: they already have the consumer eyes on their products and they have the financials to operate at a loss for years.
I just wonder how long it'll take local models to be good enough for 99% of use cases. It seems like it has to happen sooner or later.
My hunch is that in five years we'll look back and see current OpenAI as something like a 1970's VAX system. Once PCs could do most of what they could, nobody wanted a VAX anymore. I have a hard time imagining that all the big players today will survive that shift. (And if that particular shift doesn't materialize, it's so early in the game; some other equally disruptive thing will.)
In my experience with Gemini, most of its capabilities stem from web searching instead of something it has already "learned." Even if you could obtain the model weights and run them locally, the quality of the output would likely drop significantly without that live data.
To really have local LLMs become "good enough for 99% of use cases," we are essentially dependent on Google's blessing to provide APIs for our local models. I don't think they have any interest in doing so.
I agree 100%. Often when I use increasingly powerful local models (qwen3.5:32b I love you) I mix in web search using search APIs from Brave, Perplexity, and DuckDuckGo summaries. Of course this requires that I use local models via small Python or Lisp scripts I write. I pay for the Lumo+ private chat service and it has excellent integrated search, like Gemini or ChatGPT.
EDIT: I have also experimented with creating a local search index for the common tech web sites I get information from - this is a pain in the ass to maintain, but offers very low latency to add search context for local model use. This is most useful with very small and fast local models so the whole experience is low latency.
That's totally not my experience. The AI component (as opposed to the knowledge component) is really what makes these models useful, and you could add search as a tool. Of course for that you'll be dependent on a search provider, that's true.
This is actually so ironic. Corporations spent fortunes to design cool websites, but what people really want is structured, easy to read information in the context they want.
So flow is you type search query to Gemini, Gemini uses Google search, scans few results, go to selected websites, see if there is anything relevant and then compose it into something structured, readable and easy to ingest.
It's almost like going back to 90s browsing through forums, but this time Gemini is generating equivalent of forum posts "on the fly".
Unless you can provide a (community) curated list of sources to search through (e.g. using MCP). Then I think local models may become really competitive.
Taking the opposite side of that bet, here is why:
* even if an openweight model appears on huggingface today, exceeding SOTA, given my extensive experience with a wide variety of model sizes, I would find it highly surprising the "99% of use cases" could be expressed in <100B model.
* Meanwhile: I pulled claude to look into consumer GPU VRAM growth rates, median consumer VRAM went 1-2GB @ 2015 to ~8GB @ 2026, rougly doubles every 5 years; top-end isn't much better, just ahead 2 cycles.
* Putting aside current ram sourcing issues, it seems very unlikely even high-end prosumers will routinely have >100GB VRAM (=ability to run quantized SOTA 100b model) before ~2035-2040.
Even with inflated RAM prices, you can buy a Strix Halo Mini PC with 128GB unified memory right now for less than 2k. It will run gpt-oss-120b (59 GB) at an acceptable 45+ tokens per second: https://github.com/lhl/strix-halo-testing?tab=readme-ov-file...
I also believe that it should eventually be possible to train a model with somewhat persistent mixture of experts, so you only have to load different experts every few tokens. This will enable streaming experts from NVMe SSDs, so you can run state of the art models at interactive speeds with very little VRAM as long as they fit on your disk.
There will be companies producing ICs for cheap models, like Taalas or Axelera.ai today. These models will not be as good as the SOTA models, but because they are so fast, in a multi-agent approach with internet/database connectivity they can be as good as SOTA models, at least for the general public.
You can turn a local model on and off as needed, and it will still function as expected. If you turn off your self-hosted server, you don't get email.
With self-hosted email, you need persistent infrastructure and domain knowledge to leverage it. With a local model, you just click a button and tell it what to do.
With email, there is a necessary burden to outsource. Your local model is just there like Chrome/Edge/Safari is just there, there is no burden.
But AI is not about connectivity. Local models are just about as useful without an internet connection. Also, the hardware can fit in a small enclosure.
5 years is a bit optimistic. I have no desire to use anything dumber than Claude - but I doubt I'll need something much smarter either - or with so much niche knowledge baked in. The harness will take care of much. Faster would be nicer though.
That still requires a pretty large chip, and those will be selling at an insane premium for at least a few more years before a real consumer product can try their hand at it.
Coding, via something like Claude or Codex, will likely always be something best done by hosted cloud models simply because the bar there can always be higher. But it's already entirely possible to run local models for chat and research and basic document creation that can compete perfectly fine with the cloud models from 6 months to a year ago. The limitation at this point is just the cost of RAM.
This week's released of the new smaller Qwen 3.5 models was interesting. I ran a 4-bit quant of the 122b model on my NVIDIA Spark, and it's... pretty damn smart. The smaller models can be run at 8-bits on machines at very reasonable speeds. And they're not stupid. They're smarter than "ChatGPT" was a year or so ago.
AMD Strix Halo machines with 128GB of RAM can already be bought off the shelf for not-insane prices that can run these just fine. Same with M-series Macs.
Once the supply shocks make their way through the system I could see a scenario where it's possible that every consumer Mac or Windows install just comes with a 30B param or even higher model onboard that is smart enough for basic conversation and assistance, and is equipped with good tool use skills.
I just don't see a moat for OpenAI or Anthropic beyond specialized applications (like software development, CAD, etc). For long-tail consumer things? I don't see it.
Yeah, post-Moore's Law anyway. But there could also be real breakthroughs in model architecture. Maybe something replaces transformer with better than quadratic scaling, or MoE lets smaller models and agent farms compete, or, who knows....
Yesterday I asked mistral to list five mammals that don't have "e" in their name. Number three was "otter" and number five was "camel".
phi4-mini-reasoning took the same prompt and bailed out because (at least according to its trace) it interpreted it as meaning "can't have a, e, i, o, or u in the name".
Local is the only inference paradigm I'm interested in, but these things have a way to go.
I don't really see the problem here. Yeah, we know that these models are not good for actual logic. These models are lossy data compression and most-likely-responses-from-internet-forums-and-articles machines.
This kind of parlor tricks are not interesting and just because a model can list animals with or without some letters in their names doesn't mean anything especially since it isn't like the model "thinks" in English it just gives you the answer after translating it to English.
These are funny, like how you can do weird stuff with JavaScript language by combining special characters, but that doesn't really mean anything in the grand scheme of things. Like JavaScript these models despite their specific flaws still continue to deliver value to people using them.
Models will always struggle with this specific task without tool use, because of the way they tokenize things. I think a bit of prompt engineering, asking it to spell out each work or giving it the ability to run a “contains e” python function on a lot of animal names it generates or searches for solves this.
Lots of local ai use cases I think are solvable similarly once local models get good at tool use and have the proper harness.
I think this is the best article on open AI that I've ever read. A lot of content these days will try to paint OpenAI in sensational ways that really doesn't get to the bottom of whether open AI has an economic mode, and this article does a very thorough job of explaining why OpenAI doesn't have power like the other platforms.
And so this goes back to my theory that open AI's execution is basically to get it itself in a position where the market cannot afford to have it implode. Basically, it wants to or it needs to be too big to fail. And I think we're already kind of seeing the politicization, if you will, sort of the rocket race between two superpowers or large powers on the AI front, and I think that Might be a viable strategy.
I don't see OpenAI being too big to fail happening, the public is already very skeptical of AI. Also, there are other options available and therefore not a national security issue. Finally, OpenAI failing has no impact on employment or like societal disruption. In fact, it may increase employment if OpenAI fails.
The only other way to reach too big too fail status is if allied countries risk collapse if it goes under ( like the big banks in the financial crisis ) which I don't see happening either.
Yeah, I was a bit surprised that the author didn't mention that facet of Open AI. It did mention infrastructure goals, but the reality is that Open AI's infrastructure spending commitments have inflated the stock prices of quite a few hardware companies (like Micron and WD) and caused a strain on the market.
The real danger here is how over-leveraged Open AI is. No other AI player is as exposed. Their massive spending commitments are all precariously balanced on the other end by their user base, and if that evaporates, the whole thing will fall apart and that could crash the stocks of other players ...and by crash, I mean bring them down to a realistic value. But the economy is counting on this to work, which is why I believe that Open AI's strategy here really is to make the market exposed to Open AI's risks.
Hopefully this is on-topic: I would hope that some people would opt for private chat services. I evaluated both Proton’s Lumo+ and DuckDuckGo’s Duck.ai services. I like both services but only wanted to pay for one and I chose Lumo+ because chat history is stored with my Proton data and is available in all my devices, Duck.ai stores chat history on current access device. Both services are also very usable with their free plans.
At least some of us in HN talk about limiting the data we give to Facebook, Google, Microsoft, etc. Isn’t it just as important to limit what we share with non-privacy preserving AIs?
Note: tech friends have asked me how I can use slightly weaker AI models and be happy about it: I still use Gemini Plus (and Anthropic via AntiGravity) for technical work: everything I do as a software developer is open source and all of my writing (20+ books) is Open Content so I don’t care about privacy and being direct-marketed based on my tech work. To me it makes sense to use the best AI just for tech work and a private AI for everything else. Think about this if a family member has a serious health problem, or something else private: do you want to use open web searches and open AI chats, or do you want to use private web search and private AI access? Why not make privacy your default, except in special situations?
> DuckDuckGo's Duck.ai services ... what we share with non-privacy preserving AIs.
Duck.ai's Privacy Policy goes:
As noted above, we call model providers on your behalf so your personal information (for example, IP address) is not exposed to them. In addition, we have agreements in place with all model providers that further limit how they can use data from these anonymous requests, including not using Prompts and Outputs to develop or improve their models, as well as deleting all information received once it is no longer necessary to provide Outputs (at most within 30 days, with limited exceptions for safety and legal compliance).
This is not much different to the BigLabs, tbh.
Otoh, privatemode.ai, confer.to, trymaple.ai are at least attempting Apple AI-like confidentiality.
That's a fair point, but DuckDuckGo has been a privacy champion for years, so I would give them far more weight in actually adhering to these policies as a middle-man than to directly trust the others. The priorities are different.
I have a family member with a serious health problem, and I've been using Claude code to put together a very comprehensive medical dossier.
I'm not worried about the privacy aspect though many suggest that I should be. The power the dossier has given them to navigate the medical industry in the United States has been absolutely incredible. They don't have to be stuck when a random doctor who has never heard of their illness suggests that they might be overreacting. They can simply find someone who will help them. They can talk, in medical lingo, about their test results and discuss them with the doctor on equal footing.
I'm not sure this would've been nearly as successful without Opus 4.5/4.6 driving the harness. I'm not also not sure what real privacy risk there is here; it all sounds very theoretical.
There are also encrypted AI chatbots like Tinfoil and Confer that E2E encrypt all data to a secure hardware enclave. I also use Claude and OpenAI for non-privacy needing tasks, but use Kimi-k2 on tinfoil when I need privacy. Kimi-k2 feels close enough to SOTA so I'm happy with it.
1) the opportunities for vertical integration are huge. Anthropic originally said they didn’t want to build IDEs, then realized the pivot to Claude Code was available to them. Likewise when one of these companies can gobble up Legal, Medical, etc why would they let companies like Harvey capture the margins?
2) oss models are 6-12 months behind the frontier because of distillation. If labs close their models the gap will widen. Once vertical integration kicks off, the distillation cost becomes higher, and the benefit of opening up generic APIs becomes lower.
I can imagine worlds where things don’t turn out this way, but I think folks are generally underrating the possibilities here.
If OSS models are 6-12 months behind, it means sometime during 2026, we'll see a model that is on par with the likes of GPT 5.2/Opus 4.5.
For code generation specifically, the performance level of this is going to be more than enough for this customer base. What does Anthropic do then to justify $200/mo price sticker? Better model? Just how much better? Better tools? Single company can't compete with the tools entire OSS can produce.
I would be unable to sleep if I was running OAI / Anthropic.
If capabilities stop increasing for some reason, then yeah, Anthropic is screwed.
If METR task times double twice into the multi-day range in 12 months, then it’s plausible to me that Anthropic can charge $1k/mo or more by automating large chunks of the SWE role. (They have 10x’d their revenue every year, perhaps “value of enterprise contracts” is a better way of intuiting their growth rather than “$/seat” since each seat gets way more productive in this world-branch.)
The question is always about performance plateau. If LLM performance plateaus, then OSS models will catch up. If there isn’t a plateau, then I can simply ask the super intelligent AI to distill itself, or tell me how to build a clone.
It’s ironic, if the promise of AGI were realized, all knowledge companies, including AI companies, become worthless
> I can simply ask the super intelligent AI to distill itself,
I notice I am quite confused by this point. Why would you expect a super-intelligent AGI to honor your request, which would be at least a request to breach your contract with the AI provider, if not considered actively dangerous by the AI itself?
The smarter the AI, the less likely you should expect to be able to steal from it.
> or tell me how to build a clone
Step one: acquire a $100b datacenter.
Step 2: acquire a $100b private dataset
Step 3: here is the code you’d use to train Me2.0.
I don’t think this knowledge helps in the way you think it does.
I actually think that plateauing is the best case scenario for big labs.
I think there are three broad scenarios to consider:
- Super-intelligence is achieved. In this scenario the economics totally break down, but even ignoring that, it’s hard to imagine that there are any winners except for the the singular lab that gets here first.
- Scaling laws hold up and models continue to get better, but we never see any sort of “takeoff”. In this scenario, models continue to become stale after mere months and labs have to spend enormous amounts of money to stay competitive.
- Model raw capabilities plateau. In this scenario open source will catch up, but labs will have the opportunity to invest in specific verticals.
I believe that we’re already seeing the third scenario play out, but time will tell.
To go vertical they’d need to illustrate the value-add, a problem that the vertical competitors already have. Why use Claude for Accountants at $300/month when regular Claude will do the same thing for much less? The stock answer is that Claude for Accountants keeps your data more secure and doesn’t train on it. But a) I think the enterprise consumer is much less likely to trust a model creator not to stick its hand in the cookie jar than a middleman who needs the trust to survive, and b) the vertical competitors typically don’t use the absolute most up-to-date models in their products anyway, so why not just go open-source and run everything in-house? 6 months is a long time in tech, but it’s the blink of an eye in most white-collar professions.
Once the majority of work at a company can be done by AI, Anthropic has an alternative revenue stream to selling AIs to that company--directly competing with that company with a completely integrated AI system. There's of course many barriers to entry/various advantages of incumbents--but it's possible to see a world in which the company selling the AI has a huge advantage too.
The point is that in this hypothetical you can get public access to Claude Opus 6, but they internally use Claude Opus 7 (Accounting Finetune) which is both cheaper to operate and higher IQ.
So they (or their wholly owned subsidiary) can sell accounting services cheaper than anyone on the outside.
Regarding the diffusion/distillation time, I assume it gets harder to distill in the world where frontier labs don’t give API access to their newest models.
BTW the distillation (or accusations of it) seems to go both ways. I've seen multiple reports of people asking Claude what model it is -- in Chinese -- and having it answer that it's DeepSeek.
I think it’s very plausible that the OSS models are being distilled too, but note that it’s asymmetrical.
You can’t get an Opus 4.5 by distilling from DeepSeek. What you might be able to get is a slightly more cost-effective training data generation pipeline, or something along those lines.
In the other direction, my belief is that DeepSeek could not have been trained without distilling from US labs. They simply didn’t have the compute to do the pre-training required.
Tech has been trying to "gobble up" legal, medical, etc for decades. I'm quite skeptical a newcomer with a powerful model will be able to penetrate them, especially while selling those incumbents access to the same models they are building on.
> Tech has been trying to "gobble up" legal, medical, etc for decades
This time it’s different, obviously.
> especially while selling those incumbents access to the same models they are building on.
In the extreme, i think it’s plausible that frontier labs basically stop selling any access to their leading models. Whatever you make available by API will just get distilled. In the vertical integration world, the only way you get access to these models is by contracting with a company to buy a product (requirements in, code/decisions out) rather than direct conversation with the AI.
I don’t think they would unship Opus 4.6, but there isn’t a strong incentive to compete on chatbot intelligence in this world.
After trying out Pi, I really don't know what 'vertical integration' Claude Code offers. And Pi isn't even the most popular alternative (I think it's OpenCode rn).
As far as I can tell Google Gemini has the best overall integrations (Android, WearOS, Google Home) with the only voice recognition that actually works (Gemini Live).
Anthropic Claude has the best integrations with coding; what would make sense is for them to focus on that segment.
Other AI companies don't have anything really compelling. Meta has a model that's fully open-source, but then that's not particularly useful outside of helping them remain somewhat relevant, but not market-leading.
If you haven’t used codex with gpt-5.3-codex (high or xhigh) you are missing out. Claude is still good at conversations but boy I can have codex go at a problem and it does better than Claude almost all the time. Front end and product UX Claude is slightly better but given the very very generous limits of codex, they are the best bang for buck
this is my experience as well, just cancelled my claude subscription as I'm tired of it the 5 hour window being filled up within 30 minutes of use, and not even fixing the problem that codex finds almost immediately. also found for frontend that gemini 3.1 pro is better than the rest if you really play with it.
Has it been sped up at all? Last time I used codex (which was with 5.1 I think), it was pretty slow. I mean, it did a fantastic job at figuring out hard bugs across multiple languages ("why is this image not lining up in this server-rendered template?"; Python, JS, CSS, and the template lang) but it took quite a long time. Long enough that I wouldn't want to use it for anything but the most complex things.
This thing about openai brand is changing fast. In the dev circles I'm part of, everybody dislikes OpenAI and prefer Claude. How long it'll take for the same to happen with the normies?
The thing is though, Google Gemini is pretty good and it's not super hard to switch to and, the real moat, Google can just keep improving, integrating Gemini, and gathering customer while just waiting for OpenAI to go bankrupt. Basically, everyone on the planet has to pay OpenAI to keep them in business. If they don't get the vast majority of the market OpenAI can't pay their bills. Google is going to just starve OpenAI out.
> Anthropic Claude has the best integrations with coding; what would make sense is for them to focus on that segment.
the problem with coding is the value is really in the harness and orchestration both of which are accessible to the opensource community. ClaudeCode isn't that big of a deal unless Anthropic makes it so that you can only access the models that ClaudeCode uses through ClaudeCode. If not, then projects like pi and opencode have the advantage in the long run. Also, these harnesses being node modules (of all things) make them very easy to reverse engineer with the help of... claudecode ironically.
I speak native English and barebones high school Spanish. I recently visited Costa Rica and almost every time there was a language barrier issue (unknown word or phrase), the local folks opened ChatGPT, said what they were trying to say in Spanish and then had ChatGPT convert it to English. It was everywhere.
A cool use case; you can tell ChatGPT voice to act as a translator. When they speak Spanish, translate it to English. When you speak English, translate it to Spanish.
I've had better experience with LLMs translating than any bespoke translation tool, oddly enough. LLMs seemingly have a very good handle on regional varieties. As an example, I've never found a good translator for Lebanese/Syrian Arabic dialects, but ChatGPT was able to easily translate for me, even getting right some lesser used rural accent quirks which I didn't even know how to translate (similar to something like "y'all" in english).
To be fair, I wasn't using it in the way the parent comment described, for me I said: "this person speaking Lebanese/Syrian Arabic said something that sounded like [try my best to replicate the sentence]. What did they most likely mean?" and got a pretty much spot-on answer.
I wonder if this ability translates to other languages, but I wouldn't be able to tell. My Arabic is "good enough" to tell that the translations I got were good, but I'd be interested to here from someone who knows more if, for example fuzhounese translation is any good.
When OpenAI starts requiring a payment, or showing an ad before it starts translating, will they continue? Or will they use the Google Translate app, which can do this locally? (Or for that matter Gemini or Grok or whatever?)
Google Translate has been doing this forever and people in countries like Turkiye have been using it for a while. The usecase you're talking about is not exactly an LLM use case tbh.
And yet people are using it for that, even if it's not rational. I use ChatGPT for some things that would be easier and better to do with other tools out of habit.
I have done that at my home. My wife calls maids. They are there. I need to go to restroom. Ask my wife. She is struggling to communicate. It took me 3 seconds to realize ChatGPT could help. And it did.
Nice that ChatGPT does that, its also true that Google Translate and other APPs have had this functionality for a decade or more. I was getting live German translated on my phone in 2015 with no problems.
These sorts of doom articles are interesting in that they are from the perspective of tech company valuations. Why is this the important perspective?
For the humanity perspective, this doom is very optimistic. It says that these LLMs currently disrupting the platforms cannot themselves be the next platforms.
Maybe no one will have 'the ability to make people do something that they don't want to do' sort of power with this next stage in computing.
These very valid points apply to all companies trying to make money off of proprietary models, which means margins are going to collapse in a vicious price war that will make Uber vs Lyft seem tame.
As margins collapse capex will collapse. Unfortunately valuations have become so tied to AI hype any reduction in capex will signal maybe the hype has gotten ahead of itself, meaning valuations have gotten ahead of themselves. So capex keeps escalating.
None of this takes into account the hoarding effects at play with regards to GPU acquisition. It's really a dangerous situation the industry is caught in.
Companies use to hoard talent. Now they are hoarding compute, RAM, and GPUs.
Deepseek showed that there are possibly less expensive ways to train, meaning the future eye watering expenses may not happen.
Bigger models may not scale. The future may be federations of smaller expert models. Chat GPTX doesn’t need to know everything about mental health, it just needs to recognize the the Sigmund von Shrink mental health model needs to answer some of my questions.
Echoing the other comment they showed another big thing which is that the output if an AI model is the AI model. If you mass prompt scrape their AI you can recreate it almost exactly.
Very dangerous if you think about it that the product itself is the raw building block for itself.
Openai spends 1B$ on their model, releases it and instantly it gets scrapped by a million bots to build some country or company their own model.
Well there's the whole race to ASI thing. Whoever gets there first, the world is theirs. The thing will learn how learn, an intelligence feedback loop, make its own apps, find more efficient algorithms, deploy itself to more locations, bankrupt all competitors, embed itself in everyone's lives, and create a complete monopoly for the parent company that can never be touched. Until it goes rogue anyway.
(Aside, it's interesting how perceptions of these things have changed in one year: a whole article on OpenAI's future that makes no mention of AGI/ASI)
Because it's a fantasy for an unknown amount of time. 1 year? 10? 50? Never? There hasn't been a single proper breakthrough in continual learning that would enable it. Anyone that studies CL will also get super pissed at it the problem and solution counteract each other to our current understanding but a fruit fly does it no problem!
Seems like anthropic is the only company that really believes in AGI still, considering their neglect of the consumer market and continued worries about AI ethics
I don't think "believes in" is the right choice of words. It's more like "can't rule the future possibility completely out so we should at least take some precautions", which seems entirely reasonable and it's a shame not all of these companies are doing so.
ASI still runs at finite speed and is limited by its hardware, and speed of its interactions with the real world. It won’t be able to recursively improve itself overnight if it only generates 10 tokens per seconds, and a second company could very well train one of its own before the first one has time to do much.
You're not thinking of the second order meta system here. ASI isn't just one instance of an LLM responding to you in a session. It's the datacenter full of millions of LLM interacting with millions in parallel.
> Many people say we’re at AGI already and I’m wondering why everyone hasn’t died yet.
That’s like saying “many people say the Earth is flat and I’m wondering why anyone hasn’t fallen off the edge yet”.
“Many people say” doesn’t translate to reality. Maybe AGI will kill us all, maybe it won’t (I think we’re doing a fine job of that ourselves, no need for a machine’s help), but we’re definitely not at AGI, except in the minds of a few deluded people (or scammers).
Yes, just like the first person who will invent perpetual motion. /s
PS: to be clear, I'm not saying it's impossible but so far, just like perpetual motion or the Fountain of Youth it's an exciting idea anybody can easily understand yet nobody solved since it's been phrased out. It's not a solved problem and assuming it suddenly is is simply a (marketing) lie.
I think the threshold is way below self improve at 0.1% per day. I wonder what is it? At 0.1% is already going to eat the world a couple of months I think
Ever since OpenAI stuck the "Memory almost full" ad banner at the bottom of every chat, I've moved away from them. I have Grok in my car, Alexa+ on my alexas, Gemini Plus from my Google Workspace account, Microsoft Copilot at work, Claude Code because I like it, Opencode because it's free enough -- by spreading my chats around I'm not beholden to any single of them.
None of these can't be moved away from immediately. Even with my github repos, I use Antigravity, Claude Code, Opencode, and I might try Codex. I use one of them as a primary more than the other, but they're as close to interchangeable as possible.
If Codex 6.0 is better than Opus 4.9, things will flip. While OpenAI has too many common enemies and trying to box them into a consumer company, they are equally enterprise focused. They need to absolutely do well with foundation model - everything else depends on that.
Well, codex is better than opus right now. I have both subscriptions, and use claude for grunt work + codex for reviews. Codex is comparable at code writing but does much better with tools, skills and ad hoc investigations, say, lauching emacs and inspecting internal emacs state on the go.
Same, I also have both subscriptions (100 Max and 200 Pro), and I am considering canceling MAX plan but would give it another month on watch.
The doomer sentiment is quite baffling to me, what trouble is OpenAI in? Definitely not after GPT 5.3. They have the model and they have the compute, people just don't realize it yet.
Might be I am in a twitter bubble, most people seem already team Codex
I keep hearing about how the app integrations will be where the AI value is and then I see the actual app integrations and they are between useless and mildly helpful.
From what I can see Anthropic's big bet is that they will solve computer use and be able to act as an autonomous agent. Not so sure how fast they will progress on that. OpenAI on the other hand - I have no idea what they are planning - all I'm reading is AI porn and ads.
Google seems to be lackluster at executing with Gemini but they are in the best position to win this whole thing - they have so much data (index of the web, youtube, maps) and so many ways to capitalize on the models - it's honestly shocking how bad they are at creating/monetizing AI products.
Google is doing a much better job integrating AI into existing products. Gemini CLI and such seem just like a way to keep the leading competitors humble (a la iOS vs android). They're also building AI tooling tailored to specific companies (like the Goldman thing just announced) and have the cloud infra to back it up. I really only see Anthropic and Google surviving in 10 years.
My father uses ChatGPT extensively. My friend, whos an electrician, but has 0 things to do with computers, even called it Chat once and I said who? Because for me its ChatGPT. He also uses it extensively. Although I would bet they won't be willing to pay, advertisements will eventually hit them. And with inference prices going down, with distilled models being used, OpenAI will profit, and people will still hapily use it for whatever random queries they have. Exposure is the currency and OpenAI will have infinites of it for the foreseeable future.
The juxtaposition of quotations at the head of this article will seem even more silly as AI progresses. The user-centric culture that Steve Jobs championed at Apple is quite orthogonal to the trajectory of artificial intelligence. AI has been under collective development for decades. Along this trajectory ChatGPT was the discovery of a viable "product". Remembering OpenAI's documented history, ChatGPT was not the result of building a tool towards solving a specific user need. It is no accident that Apple does not know what to do with AI yet. I am hoping that they can learn from Anthropic's tool empowerment lead and from the possibilities of OpenClaw, and instrument thoughtful AI integrations for their products. OpenAI can learn from them too, but they aren't in a particularly advantageous incumbent position like Apple and Google. But whatever Apple may do, it will only be a fraction of the AI story, regardless of its consumer success. Comparing the markets of OpenAI and Anthropic highlights this diversity.
> The models have a very large user base, but very narrow engagement and stickiness, and no network effect or any other winner-takes-all effect so far that provides a clear path to turning that user base into something broader and durable.
I think this is clearly wrong. Users provide lots of data useful for making the models better and that is already being leveraged today. It seems like network effects are likely in the future too. And they have several ways to get stickiness including memory.
On the broader point, I think it's right to say that OpenAI has challenges. It simply has no differentiation beyond branding and arguably there are quite a few obvious ways it messed up and lost momentum (the board fight, trying to go in every direction at once etc.)
Today you have a phone in your pocket and you have apps on your home screen. Facebook is on your home screen, Whatsapp or X or Bluesky or whatever have a place on your home screen. Google basically is the safari app on iPhone. I don't know how many people have ChatGPT on their home screen. And soon, there will be some AI in your home screen from Apple (served by Google or another big hitter)that will be an incredible advantage.
That means OpenAI either needs to build up history with users very quickly and use that as stickiness before Apple nukes that distribution. Or they need to find a way of being another device that every living person has in their pocket.
Every attempt at doing that so far has been a comical failure and the way OpenAI are behaving makes me think their attempt will be no different.
Is this a market advantage that is a moat? I don’t see why this wouldn’t be at best a few months lead over the competition. It’s certainly not meaningful to user acquisition.
Think more like what Microsoft did by being everywhere enterprises already were: integrations, admin controls, compliance posture, procurement-friendly packaging. OpenAI doesn’t need to “invent all experiences” if it can be the default inference layer that’s easiest to buy, govern, and instrument inside large orgs—especially if it can show auditors a cleaner story than “random employees piping data into a consumer chatbot.” This is the less sexy but very real wedge: the assistant becomes a governed interface to computation.
I would love to dunk on this or something, but the lesson is that it's all about distribution.
Sama is really good at that, and also.. gotta give props for a lot of forward thinking like the orb, which now makes a lot of sense to me, as non-Apple/Google proof of personhood.
In consumer search, Google paid to be the default because defaults are basically behavioral gravity. Most people don’t churn defaults. In AI, the equivalent isn’t just “the search box,” it’s the assistant that sits inside the apps where you already spend your cognitive budget—design, docs, email, IDE, CRM, ticketing, finance—so your prompts stop being little one-off spells and start being operations with permissions, audit trails, and repeatability.
OpenAI lost the race to nerds' hearts. In the latest benchmarks, OpenAI is simultaneously cheaper (like 50% less?) and scores hire in coding and tool use benchmarks (GPT-5.3-Codex trounces Opus 4.6), yet all the coders want to marry Anthropic. I don't think OpenAI understands how to sell, if they even had a product to sell.
I'm not so sure about that. There's a lot of people that were turned off by Anthropic, especially with the weekly usage limits. that in comparison to Codex is on the last side. And actually Codex is one of the few products that I think OpenAI has executed really well on. there's just no real equivalent in terms of actual usage that you can get for the same amount of money. Gemini is great, but it seems to be still in a state of flux. Way too much products stretched too thin. Anthropic is also okay, but it's very limited in the weekly usage you can get out of it.
What I also observe is Anthoropic pissed a lot of people off when they removed external tool usage from the subscription. OpenAI won some points and usage in codex. But what conclusions can you really draw from a few reddit posts...
”In browsers, the last successful product innovations were tabs and merging search with the URL bar.”
I see the point Ben is making even though there are a lot of nerdier innovations he’s skipping over — credential management, APIs (.closest!), evergreen deployments, plugin ecosystems, privacy guards, etc.
One aspect that model execution and web browsers share is resource usage. A Raspberry Pi, for example, makes for a really great little desktop right up until you need to browse a heavy website. In model space there are a lot of really exciting new labs working on using milliwatts to do inference in the field, for the next generation of signal processing. Local execution of large models gets better every day.
I think this article spends to little time on what it calls "user data". It is likely the best data pump in this segment, because it has the most 'regular' users, i.e. people who aren't IT specialists or whatever, but give the best profit when advertised to, surveilled and so on.
They'll have their guard down more often than the claudinistas and geminites, and be cheaper to somehow exploit.
I also think that more half-serious business ideas have been initially implemented against OpenAI services, i.e. most likely to fail due to a lack of proficiency in how to make an organisation work even if the core idea is sound and worthwhile pursuing.
If you were forced to choose just one of all the competing players, which is "the one" you will use?
For me, the choice is ChatGPT, not for its Codex or other fancy tooling - just the chat. Not that Claude Code or Cowork is less important. Not that I like Codex over Claude Code.
Right now? Claude, so long as they don't fold to the Pentagon's demands. It's important to me that the company at least have a pretense of ethics. If they fold, I may just use open models via DDG – I don't find code assistants very useful for my workflow anyway.
Their existing users is an edge, but that's not much for the scale they're operating at. Users are lazy and even if you tell them "Gemini is 50 % better !" if ChatGPT isn't bad they won't switch.
Isn't this kind of splitting hairs? Technically you're right, but he's obviously talking about a product that itself, independently from its underlying model, has a "strong, clear competitive lead" over would-be competitors.
Open AI seems to be jack of all trades.i randomly use chatgpt for random questions, never for a serious task. They should check how anthropic is laserfocussed on coding and b2b segment.
My experience is completely the opposite. For generic, low-complexity CRUD tasks, Codex works fine. But when it comes to complex bug fixing, it completely fails, especially with middleware pipelines and complex authentication issues. Gemini also shines, codex is absolutely terrible for complex coding.
I’ve used Claude Code almost exclusively since its release. In the last week or two, I gave Codex a spin. So far, I’m impressed. It does seem to have reached parity. And, it doesn’t run out of tokens nearly as fast as the equivalent Claude plan.
Worth noting that it’s not a winner-takes all situation. There’s definitely space for differentiation.
Anthropic is in favor with developers and generally tech people, while OpenAi / Gemini are more commonly used by regular folks. And Grok, well, you know…
We have yet to see who’s winning in the “creative space”, probably OpenAI.
As these positionings cristallize, each company is likely going to double down on their user’s communities, like Apple did when specifically targeting creative/artsy people, instead of cranking general models that aren’t significantly better at anything.
One trillion capex per year? Does that mean they need everyone on the planet to get $100/yr subscriptions to stay solvent? Without a monopoly? Or a product that most people use much?
So far it's been more like triple-digit billions per year, and most of that has been coming from the Big Tech companies' operating cash flows. Debt recently entered the picture, however.
People underestimate the lead OAI has with their post-5.2 models. The author does not strike me as someone who closely follows the progress frontier labs make in US and around the world.
It's a joint ignorance of how these frontier models get baked and what consumers want.
Many pundits think it's just a matter of scraping the internet and having a few ML scientists run ablation experiments to tune hyperparameters. That hasn't been true for over a year. The current requirements are more org-scale, more payoff from scale, more moat. The main legitimate competitive threat is adversarial distillation.
Many pundits also think that consumers don't want to pay a premium for small differences on the margin. That is very wrong-headed. I pay $200/month to a frontier lab because, even though it's only a few % higher in benchmark scores, it is 5x more useful on the margin.
Agreed, compare the frontier models from Google and OAI. It’s like night and day. Anyone who says “the tech has caught up” has not spent even one day using Gemini 3.1 to try and accomplish something complicated.
> what a platform really achieves is to harness the creative energy of the entire tech industry, so that you don’t have to invent everything yourself and massively more stuff gets built at massive scale
I hear this, but every time I look the platforms have captured another use case that the startup ecosystem built (eg images, knowledge summarization, coding, music).
The sector is already littered with the corpses of the innovators that got swallowed by the platforms’ aggressiveness to do it all.
I have only dabbled with Claude and other AI tools, but from what I can tell, only ChatGPT has folders and a robust organization system. (Someone correct me if I’m wrong here.)
This matters a lot to me, as I use AI as something of an ongoing project organizer, and not purely for specific prompts.
So at least for me, it would be a huge hassle to move to another platform, on par with moving from one note-taking software to another (e.g., Evernote to IA Writer.)
All they need to do is fund thousands of vibe coders to create apps and utilities for people using their model.
Like, why do I STILL have to do taxes and accounting with external tools? Why doesn't OpenAI have their own tax filing service for the people?
OpenAI should just drop their API service and build everything themselves. It's exactly what they did with ChatGPT. Build thousands of things, not just a few.
A very obvious and likely to happen strategy is to turn the emotional manipulation dial up. Make users more dependent on validation and attention the model provides.
They're already doing it, but wonder how far they'll take it.
> There is no equivalent of the network effects seen at everything from Windows to Google Search to iOS to Instagram, where market share was self-reinforcing and no amount of money and effort was enough for someone else to to break in or catch up.
The main direct network effect is that Google uses heuristic data from users to improve their search rankings. (e.g. which links they click, whether someone returns quickly to Google after clicking on a link, etc)
Other factors that favor Google at scale:
- Sites often allow only the biggest search engine crawlers and block every other bot to prevent scraping. This has been going on for more than a decade and is especially true now with AI crawlers going around.
- Google search earns more per search than competitors due to their more mature ad network that they can hire lots of engineers to work on to improve ad revenues. They can also simply serve more relevant ads since their ad network is bigger.
- Google can simply share costs (e.g. index maintenance) among many more users.
This is confirmation bias. HN and other tech people are focusing on the programming aspect of AI more than anything else. The average user does not use it for that, and they don't care. ChatGPT became something like Kleenex.
Kleenex was exactly what I had in mind when reading other comments. And just like Kleenex, where people use whatever tissue they find and forget the word "tissue" even exists, ChatGPT seems to be becoming a genericized term that just means "AI chatbot."
ChatGPT is not OpenAI's product, it's the demo. The product is selling their technology to tens or hundreds of thousands of companies that embed it in e.g. customer support chat services.
The WH has said it hasn't approved any sales, but it's not clear China is buying, and it seem they are making good progress on their huawei ascend chips. If China is basiclly at parity on the full stack (silicon, framework, training, model), and it starts open weighting frontier models at $0.xx/M tokens, then yeah, moat issues all around one would imagine? Not surprised to see Anthropic complaining like this: https://www.anthropic.com/news/detecting-and-preventing-dist... - but I don't know how you go back from it at this point?
Not surprising, Nvidia's margin was just a huge incentive for companies/countries to develop their own solutions. You don't have to be 100% as good if you're 80% cheaper. It's unsurprising that this is being driven by Chinese companies/labs who often have a lot less funding than the US, and the big tech companies (Google, Microsoft, Amazon) who will benefit the most from having their own compute.
I've never believed in Nvidia's moat, and it seems OpenAI's moat (research) has gone and surprisingly is no longer a priority for them.
It seems like it’s really only China that’s pursuing the route of doing more with smaller/cheaper models, too, which also has a lot of potential to give the whole bubble a good shake.
To me it seems like the most obvious thing to do. More efficient models both make up for whatever you lost by using cheaper hardware and let you do more with the hardware you have than the competition can. By comparison the ever-growing-model strategy is a dead end.
Feels a bit crazy saying this but I can imagine a weird future where we have some outlawed Chinese tokens situation under some national security guise. No clue how that would work but nothing surprises me anymore.
Nvidia's margins are a wake-up call for anyone reliant on their tech. As companies in places like China pursue self-sufficiency, the competitive landscape is shifting quickly, opening up space for innovation from unexpected sources.
it seem they are making good progress on their huawei ascend chips
This is interesting to me. I thought that the reason for deepseek delay was because of the insistence ( by the politicians) to use huawei chip[0]. But that was last year August.
Anthropic are making a very convincing play for business and "enterprise" customers - first with Claude Code and now with Cowork and especially Claude for Excel. The revenue growth they've announced has been extremely impressive over the past year.
X has only brand recognition right now, and an extremely toxic one.
Big customers may buy but won't give them logos, people who are offended by Musk's worldview won't pay them either. You don't do well with a toxic brand: just look at Ye having to buy full page apologies ads to try and sell a record.
It's funny you say that, I thought this would be an article about how Anthropic have managed to produce a better (coding) product than OpenAI despite having 1/10th of the funding.
The new versions of Opus (4.5 and 4.6) are absolutely amazing - first time I've felt it necessary to throw hundreds of dollars in a single month at Cursor.
I heard similar things about the older models too (Sonnet 3.5 beating GPT-4 etc.) but sadly only jumped on the Cursor train in the last 12 months or so.
The problem is not the models, is the moat and budget. Google and X still have money and are profitable, all the other AI companies are losing billions per year.
And customers will happily switch from one model to another in a heartbeat.
> Personally I only see Google (Gemini), X (Grok) and the Chinese models having a chances to still be alive in 1-2 years.
I'd make it more general - the only AI tokens providers that will last past the bubble are those companies that are already self-sustaining via other product channels.
Any company that has AI as their one and only product aren't going to survive.
Tech companies are one of the jewels in America's (USA's) crown. If we build a bunch of huge AI companies, rivals will probably continue to release open AI models which undermine the US's influence in the world.
> Every few weeks they leapfrog each other. There is variation within those capabilities, it’s possible to drop off the curve (Meta, for now) or fail to get onto it (Apple, Amazon, Microsoft, for now), or remain six months behind the frontier (China), or rely heavily on other people’s work (China, again)
I really dislike this narrative where it's always China = bad, and US companies = good.
These labs all copy from each other. OpenAI and Anthropic have "distilled" each other models too and routinely poach key researchers from competitors. Not only that, there's evidence Sonnet 4.6 has heavily distilled Deepseek R1 too, in fact, if you ask Sonnet 4.6 in Chinese who it is, it will tell you it's a Deepseek model.
Chinese are the only ones publishing papers on their models non stop.
The whole AI race is entirely based on blatant copyright infringements and copying each other.
I'm not a huge fan of OpenAI as a company, but I subscribe to ChatGPT. I regularly try put the competition, but (for me) ChatGPT deliveres better results.
Give me an open source or non-American product that delivers the same quality, and I'll switch in an instant.
FWIW, this is how capitalism is supposed to work! Competition is driving AI forward at a fantastic pace!
Sometimes I like to imagine what this would be like if the technology had appeared 25 years ago.
First off, nonetheless open publishing stuff. Everything would have been trade secrets.
Next off no interoperable json apis instead binary APIs that are hard to integrate with and therefore sticky. Once you spent 3 or 4 months getting your MCP server setup, no way would you ever try to change to a different vendor!
The number of investors was much smaller so odds are you wouldn't have seen these crazy high salaries and you wouldn't have people running off to different companies left and right. (I know, .com boom, but the .com boom never saw 500k cash salaries...)
Imagine if Google hadn't published any papers about transformers or the attention paper had been an internal memo or heck just word2vec was only an internal library.
It has all been a net good for technological progress but not that good for the companies involved.
Could they have even trained the models 25 years ago? Wikipedia was nothing close to what it is today and I know folks here like to mourn the fall of the open web, but it's still orders of magnitude larger today than it was in 2001. YouTube, so many information stores that simply didn't exist then.
Maybe not 25,but IBM Watson beat humans at Jeopardy over 10 years ago. The technology has been there, the difference is the willingness to burn money on it in hopes of capturing exponential revenue from disrupting industries.
Obviously the costs have come down but if IBM felt like burning 100 Billion in 2012 I'm pretty sure they could have a similarly impressive chat bot. Just not sure how they would have ever recouped the revenue.
The book archives are a big one as well, all the journals that have been published digitally throughout the 2000s, and all the newspapers.
Though with some types of models (specifically voice) it has been discovered that a smaller high quality dataset is better than a giant dataset filled with errors.
sammy boy needs to pull a rockefeller and buy up all the competitors. Maybe that's what all these backroom deals about datacentre investment will amount to...
This was poorly worded but indeed rockefeller was the richest man ever by selling a commodity. But he did it by merging with all his competitors. Not sure Altman could pull that off here because most of the other models are attached to massive tech co's that can use AI as a loss leader for other profitable services.
This article is significantly better written than most anti-OpenAI/AI articles, and for that I am really grateful. I am generally an AI booster (lol), so I am happy to read well-considered thought pieces from people who disagree with me.
That being said...
> The one place where OpenAI does have a clear lead today is in the user base: it has 8-900m users. The trouble is, there’re only ‘weekly active’ users: the vast majority even of people who already know what this is and know how to use it have not made it a daily habit. Only 5% of ChatGPT users are paying, and even US teens are much more likely to use this a few times a week or less than they are to use it multiple time a day.
This really props up the whole argument, because the author goes on to say that OpenAI's users are not really engaged. But is "only" 5% of users paying of a 8-900M user base really so inconsequential? What percentage of Meta's users are paying? Google's? I would be curious to see the author dig deeper here, because I am skeptical that this is really as bad as the author suggests.
Moving on to another section:
> If the next step is those new experiences, who does that, and why would it be OpenAI? The entire tech industry is trying to invent the second step of generative AI experiences - how can you plan for it to be you? How do you compete with this chart - with every entrepreneur in Silicon Valley?
Er, are any of these startups training foundation models? No? Then maybe that is how you compete? I suppose the author would say that the foundation model isn't doing much for OpenAI's engagement metrics (and therefore revenue), but I am not sure I agree there.
Still, really good article. I think it really crystalizes the anti-OpenAI argument and it gives me a lot of interesting things to think about.
> But is "only" 5% of users paying of a 8-900M user base really so inconsequential? What percentage of Meta's users are paying? Google's? I would be curious to see the author dig deeper here, because I am skeptical that this is really as bad as the author suggests.
The difference is in the unit economics. OpenAI has to spend massively per free user it serves. The others you mentioned have SaaS economics where the marginal cost of onboarding and serving each non-paying user is essentially zero while also gaining money from these free users via advertising. Hence, the free users are actually a net positive rather than an endless money sink.
Keep also in mind that AI has always been, and will always be, a commodity. The moment you start forcing people to convert into paying customers is the moment they jump ship at scale.
> What percentage of Meta's users are paying? Google's?
The advertiser based business model for those companies makes your question/thought process here problematic for me. Historically speaking Google and "Meta" (Facebook) were primarily advertising provider companies. They provided billboards (space and time on the web page in front of an end-user) to people who were willing to buy tht space and time on the billboard. The "free access" end-users would always end up seeing said billboards, which is how they ended up "paying" for the service.
So most of Meta/Google end-users were "paying" users. They were being subsidised by the advertising customers paying for the end-users (who were forced to view adverts). The end-users paid with interruption to the service by an advert. [0]
In that context it feels a little like you're comparing apples to dave's left foot, as OpenAI hasn't had that with advertising ............ historically [1].
--
[0]: yes ad-blockers, yes more diverse revenue income streams over the years like with phones, yes this is simplified yadayada
[1]: excluding government etc. ~bailouts~ investments as not the same as advertising subsidies, but you could argue it's doing the same thing
Yes -- but both Google and Meta didn't start off as an advertising company - they started off providing a service a lot of people liked, and then eventually added ads to it. My assumption (somewhat implicit, admittedly) is that there's no reason OpenAI couldn't do the same. I can understand why that might be controversial, though.
But honestly, if OpenAI can't figure out ads given all their data and ability, they deserve to fail. :P
You’ve missed the point completely - if the important experiences are things built on top of foundation models, where the model itself is just an API call, then you don’t need to have a foundation model for build them and the model is just commodity infra
Yes, but OpenAI has 900M+ user reach, plus staggering amounts of cash, plus early access + deep integration with the latest and greatest models. I hardly think that is tantamount to "just an API call".
Same here. I moved from claude code to codex. But switching costs are so low that I will just bounce between them depending on which one is better at the time. I think for developers at least, openai don't have stickiness.
I use Codex for stuff that touches the UI. Codex is better and faster at the backend stuff. And I usually instruct it on where to copy UI elements from.
A basic Claude Code plus a basic Codex subscription is just 40 euros and it beats a single 200 euro Pro subscription. For me at least.
The main problem with OpenAI/Anthropic is that their only moat is their models, and it has been proven that you can clone a model through distillation. Although the performance is not exactly the same, it gets very close to the original.
> The one place where OpenAI does have a clear lead today is in the user base: it has 8-900m users.
There is no way that number is an accurate reflection of the number of actual human users of their service. I could believe they have 8-900m bot/fraud accounts in their databases, maybe, but not real users.
I suspect I am one of those 1bn users by their metric. I have an account, and I sometimes query it. I also query Claude and Gemini. I have zero loyalty, if I run out of tokens on one, I will just pick up the conversation on another provider. Perhaps I am using them wrong, but the amount of babysitting I have to do anyway, I don't find it that tedious to stay on the same topic during a swap.
There's no way I would spend $200 a month on any of them, not even $20 considering how few 'tokens' you get. I can see how these tools would be useful to my workflow, but I cannot use them as they are priced 100x too high for me to be reliable.
I have a feeling that would be true for the vast majority of these AI tool users. I really am not sure how these companies are supposed to become profitable. But SV is a bit insane that way.
i used to use them that way until I got a IDE with AI and is way better for my development than copying and pasting into the chat. It can have the whole project as context,plan features with me, etc. I use it a lot in a way that I cant see why I would go to programming without it right now. It takes time to adjust to it to learn how it works and all but it's worth it
Everyone is actually underestimating stickiness. The near billion users OpenAI has is actually a real moat and might translate into decent chunk of revenue.
My wife, for example, uses ChatGPT on a daily basis, but has found no reason to try anything else. There are no network effects for sure, but people have hundreds and thousands on conversation on these apps that can't be easily moved elsewhere. Understandable that it would be hard to get majority of these free users to pay for anything, and hence, advertising seems a good bet. You couldn't have thought of a more contextual way of plugging in a paid product.
I think OpenAI has better chance to winning on the consumer side than everyone else. Of course, would that much up against hundreds of billions of dollars in capex remains to be seen.
So in summary OpenAI are basing their valuation of 285 billion on the moat of 'users won't be arsed to download a different app'???
Seems optimistic when there is very little intrinsic stickness due to learning the UI or network effects. Perhaps a little bit chat history - but not 285 billions worth.
Also completely ignoring the fact that most devices things will start to come with the same features directly built into the device/app - and the largest market will be as a commodity backend api that the eventually users won't know or care if it's a google or openai model.
As I see it, they need to be doing stuff nobody else can ( in either price or performance ), otherwise it's hard to justify the valuation.
It have worked for Google for years, and that was without even the barrier of download in app, just going to a different URL.
21 replies →
You'd be surprised that most people don't find any pleasure in comparing and trying out different software. They're looking for something which works and ChatGPT is just an amazing product. People aren't going to look for something else unless it breaks for some reason.
Most people who have a vehicle aren't trying out different motor oils, or comparing every month if they should change model, etc.
> As I see it, they need to be doing stuff nobody else can ( in either price or performance ), otherwise it's hard to justify the valuation.
Do you have a car? What does it do that no other car does?
> the moat of 'users won't be arsed to download a different app'???
don't even need to download anything, just open your browser and go to google.com to use gemini
last week-end, I've seen a non-tech friend who previously used chatGPT on his phone, just go on google to ask stuff to the AI (they have no idea it's gemini and it doesn't matter)
if you are not looking for having some kind of relationship with an AI (from what I understand people use chatGPT for this use case), but just looking for an AI to search stuff, then in my opinion you can't beat google search + gemini summary all at once for free with a single prompt
Directing your attention to Coca-Cola
[flagged]
29 replies →
I think you're right about stickyness up to a point.
Cultural defaults seem unchangeable but then suddenly everyone knows, that's everyone knows, that OpenAI is passé.
OpenAI has a real chance to blow their lead, ending up in a hellish no-man's land by trying to please everyone: Not cool enough for normies, not safe enough for business, not radical enough for techies. Pick a lane or perish.
Not owning their own infrastructure, and being propped up by financial / valuation tricks are more red flags.
Being a first mover doesn't guarantee getting to the golden goose, remember MySpace.
> Being a first mover doesn't guarantee getting to the golden goose, remember MySpace.
MySpace, ICQ, Altavista, Dropbox, Yahoo, BlackBerry, Xerox Alto, Altair 8800, CP/M, WordStar, VisiCalc, the list is very long.
22 replies →
I guess it depends on what you mean by golden goose. MySpace sold for an insane amount of money at the time and it was basically one guy, “Tom”.
Pick a lane or perish.
Literally every industry has examples of businesses that don't excel at anything and still do well enough to carry on. In fact, in most industries, it's actually hard to see any business that's clearly leading on any specific front because as soon as it becomes an obvious factor in gaining market share the competing businesses focus on that area as well.
2 replies →
First mover advantage: marketing logic or marketing legend: https://gtellis.net/wp-content/uploads/2020/09/pioneering-ad...
> Everyone is actually underestimating stickiness.
I think you're underestimating how fickle consumers are, and how much their choices are based on fashion and emotion. A couple more of these, and OpenAI will find itself relegated to the kids' table with Grok and Perplexity. https://www.technologyreview.com/2025/08/15/1121900/gpt4o-gr...
I still use perplexity. Which tool is better currently?
2 replies →
Is she paying for it? That is the only question that matters in the end.
For myself, I use LLMs daily and I would even say a lot on some days and I _did_ pay the 20€/mo subscription for ChatGPT, but with the latest model I cannot justify that anymore.
4o was amazingly good even if it had some parasocial issues with some people, it actually did what I expect an LLM to do. Now the quality of the 5.whatever has gone drastically down. It no longer searches web for things it doesn't know, but instead guesses.
Even worse is the tone it uses; "Let's look at this calmly" and other repeated sentences are just off putting and make the conversation feel like the LLM thinks I am about to kill myself constantly and that is not what I want from my LLM.
>Is she paying for it? That is the only question that matters in the end.
Don't underestimate advertising. Noone pays for Facebook or Google search. Yet the ad business with a couple billion users seems profitable enough to fund frontier LLM research and inference infrastructure as a side-gig in these companies. Google only rushed out AI overview because they saw ChatGPT eating their market share in information retrieval and Zuck is literally panicking about the fact that users share more personal details with OpenAI than on his doomscrolling attention sinks.
24 replies →
not necessarily, if openai managed to monetize free users. Could be through advertising, or integrations with marketplaces on commission (e.g. order your next Hello Fresh through ChatGPT? Get recommended a hotel?)
They could succeed where Alexa failed. A free user can even bring in more than a paid user if you look at some platforms like spotify, where apparently there is a large chunk of free users generating more income through ads than if they would pay
2 replies →
Most potential customers wouldn't ever think in terms as "justifying" a €20 purchase when the product is great.
ChatGPT (and competitors) is an incredibly high value tool, and €20 per month is nothing for somebody who wants or needs it. It's just a matter of if they use it enough to start hitting the daily limits.
2 replies →
>no longer searches web for things it doesn't know, but instead guesses.
This could very well have been a cost-reduction effort to try and simulate what it was doing before.
Somebody must think training has already looked at the web enough, or there may be too much slop now that there was no contingency for.
Then you've got tighter guardrails to make it more palatable for a wider audience.
I guess different people would draw the line differently, but when it goes from being worth money to not worth it any more that could be an enshittification effect.
Especially if things like that accelerate.
I hear the claim that people already have their conversation on ChatGPT and can't move them. I'm curious, what are these discussions like? I've never continued an old discussion, I just start a new one every time I have a question. If the discussion is long, I often start a new chat to get a blank slate. My experience is that the chat history just causes confusion.
So I'm curious to understand: What are the discussions like that people go back to and would lose if they moved to another platform?
In my experience non-technical folks quite dig the memory feature. For me that's kinda context poisoning as a service, but I know people that get value out of it (or at least strongly feel they do). Not sure how one would migrate that.
3 replies →
I'm curious from the other direction, what are the conversations like if you feel they are easy to move?
Do you have the memory feature disabled? I have the feeling this in particular is doing absolutely loads behind the scene, e.g summarising all conversations and adding additional hidden context to every request.
I can start a new chat in the UI right now, ask it what my job is, what my current project is, how many kids I have, what car I drive etc. It'll know the answer already.
I think it's this conversation history - or maybe better yet if we think of it as this "relationship" - that people are saying is going to make it hard to move.
1 reply →
Regardless of whether there is value in chat history or not, for some people it is important.
Back in the day during the music streaming wars there were tons of "move your playlists from A to B" services. Streaming services could not hold on to customers because all their playlists were on there.
I'm sure that similar services will pop up for chatbots.
Also, you can always just ask your chatbot to generate a file with your chat history, given that it's all part of the context anyway.
Health data. That’s why they’re rolling out Chatgpt Health.
yeah the 'sessions' approach is probably going to be deprecated. one continuous chat is where it's at , perhaps with some bookmarks on the side for easy access
or perhaps a thread-based chat like reddit or HN, where you can branch off an older conversation with yourself
1 reply →
"Near billion users", yet less than 5% pay them a single penny[1]. Like you said, the vast majority of these will never pay anything, but I'd argue the majority will migrate to the "next" free provider as soon as OpenAI starts inserting too many ads into the product.
I watched my partner switch from OAI to DeepSeek during the last outage and she hasn't been back to OAI since. I am skeptical there is any actual stickyness when basically all of the chatbots do the same thing for the casual user.
[1] https://www.theregister.com/2025/10/15/openais_chatgpt_popul...
Google Search has no stickiness and they managed to build a behemoth.
ChatGPT is a great product, but the lack of stickiness comes into play because there are many viable alternatives.
They’re all going to have to monetise the consumer segment at some stage, and I think that’s likely to be via ads on a freemium tier in most instances.
2 replies →
You say 5% of users pay like it’s a shockingly bad number, but that’s almost exactly the same as YouTube’s paid subscribers (125m) vs MAUs (2.5b).
Like it or not, OpenAI is building a real business. It’s obviously capital intensive, but we will see how it goes.
And no, the vast majority will not migrate. Just like the vast majority didn’t migrate away from Google after they launched ads.
I don’t get the HN urge to be the contrarian saying “that’ll never work.”
2 replies →
Anecdata point: I canceled my ChatGPT pro subscription last year over some shitty thing Altman did at OpenAI and easily moved over to Claude. The only thing I took with me was the system prompt or whatever it's called, I couldn't care less about my conversation history. I'm planning to do the same thing with my Claude subscription if Anthropic kowtows to the Pentagon. These services are not sticky at all IMO.
Anthropic already decided to do business with the "killing people" department of the government. I think the battle was lost there, rather than whether or not they cross a line in the sand they drew to act as if they're the ethical AI company despite making products that are used to kill people. I'm sure the result of this battle will be some compromise that allows the Pentagon to get whatever they want while offering a fig leaf to Anthropic to continue their ethicality show.
1 reply →
Anthropic donated $20 million to Public First Action[1], a PAC that promotes Republican Senator Marsha Blackburn and her sponsored Kids Online Safety Act (KOSA)[2], a bill that will force everyone to scan their faces and IDs to use the internet under the guise of saving the children.
The legislative angle taken by companies like Anthropic is that they will provide the censorship gatekeeping infrastructure to scan all user-generated content that gets posted online for "appropriateness", guaranteeing AI providers a constant firehose of novel content they can train on and get paid for the free training. AI companies will also get paid to train on videos of everyone's faces and IDs.
As for why Blackburn supports KOSA[3]:
> Asked what conservatives’ top priorities should be right now, Senator Blackburn answered, “protecting minor children from the transgender [sic] in this culture and that influence.” She then talked about how KOSA could address this problem, and named social media platforms as places “where children are being indoctrinated.”
If Anthropic, the PACs it supports and Blackburn get their way with KOSA, the end result will be that anything posted on the internet will be able to be traced back to you. Web platforms will finally be able to sell their userbases as identifiable and monetizable humans to their partners/advertisers/governments/facial recognition systems/etc. AI companies will legally enshrine themselves as the official gatekeepers and censors of the internet, and they will be paid to train on the totality of novel human creativity in real-time.
That will be their moat.
[1] https://www.cnbc.com/2026/02/12/anthropic-gives-20-million-t...
[2] https://publicfirstaction.us/news/public-first-action-and-de...
[3] https://www.them.us/story/kosa-senator-blackburn-censor-tran...
Where are you thinking of moving to?
2 replies →
> but people have hundreds and thousands on conversation on these apps that can't be easily moved elsewhere.
Except these aren't conversations in the traditional sense. Yes, there's the history of prompts and responses exchanged. But the threads don't build on each other - there's no cross-conversational memory, such as you'd have in a human relationship. Even within a conversation it's mostly stateless, sending the full context history each time as input.
So there's no real data or network effect moat - the moat is all in model quality (which is an extremely competitive race) and harness quality (same). I just don't think there's any real switching cost here.
This is not the case.
I use OpenAI a lot on the paid plan via the UI. It now knows absolutely loads about me and seems to have a massive amount of cross conversational memory. It's really getting very close to what you'd expect from a human conversation in this regard.
Sure the model itself is still stateless, and if you use the API then what you say is true.
But they are doing so much unseen summarisation and longer context building behind the scenes in the webapp, what you see in the current conversation history is just a fraction of what is getting sent to the model.
3 replies →
I see people who have conversations spanning months. They don't start new threads and instead go back to existing threads to continue the topic. They also reference the prior threads discussion many times.
This would feel like a switching cost for people who use the system that way.
1 reply →
ChatGPT and Gemini has cross conversation personalization. I believe the former is off by default and the latter is on.
6 replies →
> Everyone is actually underestimating stickiness. The near billion users OpenAI has is actually a real moat and might translate into decent chunk of revenue.
I’ve got a small-ish sample of friends who are regular people and use various AI chatbots because mobile phone providers now commonly bundle an AI subscription with their services. People seem to switch between Perplexity, Claude, and ChatGPT without any trouble. It does not look sticky at all to me and the half-a-percent difference in benchmarks we love to obsess about does not translate at all in increased user satisfaction.
I don't think chat history is enough for real stickiness.
But the trillion dollar question is, what is? Now that I think about it, I'd bet heavily on Google. They've got your email, your photos, your location history, yada yada. Once they're able to pull all that into AI and make a reasonably cohesive product out of it, it seems like that's what people would use by default. Plus they've got a browser, search page, and phone OS that all can lead you to their AI.
They could train custom LoRA layers to mimic your tone, encode special tokens that indicate your name and data and various facts about you and your contacts, to make output more accurate, consistent, and personalized. Lots of possibilities for increased stickiness.
Even enterprise-wise, gemini is pretty good at coding and if your company has all its docs on Google docs, that could become a pretty seamless integration. They can even build their agents to prefer GCP, or maybe make that the free tier but have other providers support be more expensive.
At some point, a reasonable business model might be "we replace your engineering team with AI plus a few Google engineers on retainer for when things get wonky," which could scale to pretty large. (Granted this sounds more like a msft power move.)
They already have all the infrastructure, all they need is a reasonable competitor to github. They really screwed up losing out to msft on that one!
It would literally take you 5 mins to set up your wife with a competing client for her needs.
Sure it's 'sticky' at least a little, but it's not a moat. A moat is a show stopper like they own you.
Just like it would take 10 seconds to buy her a Pepsi instead of her preferred Coke.
Would you?
9 replies →
Idk, habit and the devil you know are powerful as hell. Google has enshittified search nearly beyond imagination, but it's still where the vastly overwhelming majority of people search.
1 reply →
> The near billion users OpenAI has is actually a real moat and might translate into decent chunk of revenue.
People used to suggest this about MySpace.
MySpace never had close to a billion users.
3 replies →
In theory you can export your data from ChatGPT under Settings > Data Controls. In practice, I tried this recently and the download link was broken. Convenient bug I must say.
Make sure you're logged in to chatgpt.com in the same browser you're using to access that link.
1 reply →
Yahoo, altavista, askjeeves, Google
Friendster, MySpace, Facebook
Netscape, ie, chrome
Icq, aim, MSN messenger, a million other chat apps
First mover advantage doesn't last long
Very high chance that the winner in five years is a company that does not yet exist
My wife, for example, uses [Netscape Navigator] on a daily basis, but has found no reason to try anything else. There are no network effects for sure, but people have hundreds and thousands on [bookmarks] on these apps that can't be easily moved elsewhere.
See how stupid it sounds?
Given how long people have stuck with Internet Explorer, I don't think this is a good example.
2 replies →
ChatGPT has a good name. It's weird and awkward but it still rolls off the tongue. And I am saying that as a non native English speaker because the name has been migrated to other languages with the English pronunciation.
In comparison, Claude's name is very bad, it just doesn't sound right and people might mishear me when I say it. I never say "Claude" when talking to other, especially non-technical people, and instead say "ChatGPT" even though I am using Claude exclusively.
Google has another problem - they advertise their models as separate products. There is Gemini and there is Nano Banana, also Nano Banana Pro. But they are all somehow under the same product which is still called Gemini. I understand the distinction but I am sure many non-technical people find it confusing.
Claude may seem incongruous compared to the others, however it's the only human sounding name, compared to the robotic "chatgpt" or others that sound generic or bland company names (Gemini, perplexity).
They intentionally chose a more bland sounding name, as, I assume, they wanted to emphasise the "safe" nature compared to their competitors.
As more information comes out about openai, people may choose to move to for other reasons, such as
- Openai adding ads
- Openai's president donating millions to a MAGA PAC
- Openai getting closer to the US military whilst anthropic standing their ground and rejecting them.
- Openai's recent products not being at the top of the benchmarks
The choice is yours.
3 replies →
In Japan many people call it "Chappie" (チャッピー), which I think is much easier to say and less awkward, haha. I see a lot of people using it here daily.
I feel like OpenAI should lean into that.
1 reply →
They initially wanted to call it just "Gemini 2.5 Flash Image (preview)" but the Internet stuck with the anonymous codename Nano-banana from LMArena because it's interesting and quirky. Google didn't officially adopt it until several days after the public release, exactly because of what you say. Eventually, not using it in their comms got more confusing because regular people were asking how they can find this Nano banana thing everyone is hyped about.
I have heard "cloud code" many times from colleagues who do not really know what either cloud OR Claude Code is more than "stuff we should use".
1 reply →
Absolutely no enduser knows what 'GPT' stands for and if you tell them it's Generative Pre-trained Transformer they're even more confused than before.
There's better brand names out there.
1 reply →
> ChatGPT has a good name
I don't know but around here common people all say "Chatty" nowadays, and also most people if writing the correct name fail to spell "gpt" right quite often in chat.
Claude is a terrible name but Gemini is pretty good.
2 replies →
> The near billion users OpenAI has is actually a real moat and might translate into decent chunk of revenue.
> My wife, for example, uses ChatGPT on a daily basis, but has found no reason to try anything else.
Is she paying for it? Because as we have seen repeatedly in the past, paid products whither and die when Microsoft bundles a default replacement.
You need to provide a really good reason why this time its different.
I believe specifically for Microsoft, they did bundle a default replacement for chatGPT in a lot of different places (Bing chat, Copilot) which use OpenAI models! But the end product is notably worse than native interface. There is a bare-minimum-level of usability required.
For chat apps, good enough is good enough. For something as universally useful and easy to use as ChatGPT, the bar is higher. I don't want to comment on the financial feasibility, but whatever Microsoft put out has been a complete flop even when free, making ChatGPT $8 subscription seem worth it in comparison
3 replies →
I don’t know how much of an anecdote it is, but all the non-tech people with whom I talk about IA only know chatGPT. Competition is either non existent or the same thing. Among those, no one wants to pay the service, they just stop using it when limits are reached. I can’t say which users can turn the market around but chatGPT is indeed burned in the mind of many and because they don’t care about tech and are not interested in tech they won’t search for any other service it seems. Even after many discussions they don’t remember the names of other IA I told them
I would bet 100% of those people have either Apple or Android phone in their pocket. Android users already have easy access to Gemini, and Apple's Siri is going LLM soon enough as well.
Google and Apple just need to push their AI assistants hard enough, and most of the moat OpenAI has will be gone.
1 reply →
The only two models I ever hear non technical people mention are ChatGPT and occasionally Gemini
> My wife, for example, uses ChatGPT on a daily basis, but has found no reason to try anything else.
Ads might change that. If we know anything, nobody beats Google with ad based monetization. OAI is absolutely correct to be scared.
I commute on the train, I see students studying with it. I go for brunch on the weekend, I see parents consulting it while at the table with their infants. I'm at work, colleagues are using it all day. I leave work and I overhear the random woman smoking in the alleyway talking on her cellphone saying "so I asked chatgpt". It's mind-bogglingly pervasive, the last time something had such a seizmic cultural impact like this was I dunno, Facebook? And secondly, it's all one specific brand. I'm not encountering co-pilot or gemini in the meat-space.
Chatgpt is like "Jeep". My grandmother calls every suv a jeep. But they're not all jeeps. AI looks like chatgpt, but people are driving all sorts of different AIs.
I would guess OAI has no moat or stickiness beyond what governments and private companies will do to keep it afloat through equity and circular financing. Good enough AI is all most need, and they need it at the cheapest cost basis possible with the most convenient access.
Google will probably win on most of these fronts unless a coalition is formed to actively fight google at the business/government level. But, absent that, it will win out over oai and oai will probably bleed to death trying to become profitable.. whenever that happens. You'll likely see their talent and corresponding salaries shrink massively along this journey.
1 reply →
My sister uses Gemini and calls it chat gpt. It's becoming a genericide.
12 replies →
How many of those people are paying? I think many say “use ChatGPT” to mean any LLM. As you noted it seems you just see ChatGPT in the wild but that is anecdotal. It is certainly pervasive right now. But I know a lot of people currently switching to Gemini.
I personally prefer claude models for all my work. If I were them I would be very worried. They are never giving us AGI and I am skeptical they are worth .5 trillion. Their cash burn is insane. Once ads and price hikes come, people will migrate to companies that can still afford to subsidize (like Google).
Plus I heard they lowered projections recently? Sam honestly comes off as a grifter.
6 replies →
I think that's false. The cost of switching is so low that the best product will win and there's no moat.
I honestly can't see how OpenAI can possibly recoup the hundreds of billions poured into it at this point. I'd say AI assistants are no more sticky than browsers or search engines.
You might be tempted to say that Chrome or Google are sticky. But they're really not. A lot of people aren't old enough to remember the 90s when we had multiple search engines and people did switch. I know this goes against prevailing HN dogma but I'm sorry: Google is simply the best search engine. It doesn't have a magical hold on people. People aren't fooling themselves.
And Chrome? Before smartphones it was simply the better browser. Firefox used to have a much larger market share and Chrome ate their lunch. By being a better browser. Chrome was I think the first browser, or at least the first major browser, to do one process per tab. I still remember Firefox hanging my entire browser when something went wrong. I switched to Chrome in version 2 for that reason.
And now browsers are more sticky because of Chrome on Android and Safari on iOS. Safari really needs to be cross-platform, like seriously so. I know they briefly tried on Windows but they didn't really mean it.
Anyway, back to the point. I believe there's a certain amount of brand inertia but that's it. If Gemini dominates ChatGPT performance and UI/UX, people will switch so fast.
Google, Microsoft and Meta can survive the AI collapse. Apple is irrelevant (at least for now). OpenAI? Doomed IMHO.
> people have hundreds and thousands on conversation on these apps that can't be easily moved elsewhere.
I just asked it to build me a searchable indexed downloaded version of all my conversations. One shot, one html page, everything exported (json files).
I’m sure I could ask Claude to import it. I don’t see the moat.
How do you know all your conversations are in there?
Honest question I have this issue a lot with AI claims. Nobody verifies the output.
8 replies →
there is no moat also because conversation history is useless. like saying “I cant move to DDG cause Google has my search history”
1 reply →
I think that kind of inertia mostly lasts as long as there is no financial incentive to move. A ChatGPT user who is not paying anything to OpenAI is of little benefit to them, and has little incentive to switch. However if OpenAI start trying to make money off those users by adding advertising, or removing the free tier, then things may change. Google can afford to subsidize chat from their other revenue streams, but OpenAI can't.
>However if OpenAI start trying to make money off those users by adding advertising, or removing the free tier, then things may change.
Tech forums tend to be in a bit of a bubble. People said the same thing about Netflix and it just quickly became their most popular sub. People don't care about advertising unless it's really obnoxious.
The idea that people will unsub en masse once Open AI starts rolling ads is a pipe dream. And the kind of user that won't pay and won't suffer some ads is the kind of user nobody wants.
2 replies →
Why would you want to move conversations with you? I use multiple different models, I don't care about the history.
My "brain" in terms of projects, is local on my computer. I have a simple set of system rules that I need to copy.
I am not everyone, I understand that. What I try to say: don't overestimate the lock in effect of AI. I doubt there is one.
> I don't care about the history.
I've actually been using the Gemini app more because it auto-deletes old history. I like using LLMs without thinking this is going to stick around forever.
Models are relatively interchangeable for day-to-day use anyway.
OpenAI is already building complex user models. And I mean, super detailed user models - where you are from, what you do, what are your most vulnerable weaknesses, what you care about the most and everything else. This is information even the world's largest advertising company would struggle to put together across their fragmented eco-system (Gmail, Search, etc), but OpenAI has all this on a silver platter. And that scares me, because, a lot of people use ChatGPT as a therapist. We know this because of their advertising intent which they've explicitly expressed. Advertising requires good user models to work (so advertisers can efficiently target their audience) and it is the only way to prove ROI to the advertisers. "But, OpenAI said they won't do targeted ads..". Remember, Google said "Don't be evil" once upon a time too..
That's ok, we use ChatGPT only for coding. We should be good, right? Umm, no. They already explicitly expressed the intention to take a percentage of your revenue if you shipped something with ChatGPT, so even the tech guys aren't safe.
"As intelligence moves into scientific research, drug discovery, energy systems, and financial modeling, new economic models will emerge. Licensing, IP-based agreements, and outcome-based pricing will share in the value created. That is how the internet evolved. Intelligence will follow the same path."
"Intelligence will follow the same path."
https://openai.com/index/a-business-that-scales-with-the-val...
So yes, OpenAI has the best chance to win on the consumer side than anyone else. But, that's not necessarily a good thing (and the OpenAI fanboys will hate me for pointing this out).
> They already explicitly expressed the intention to take a percentage of your revenue if you shipped something with ChatGPT, so even the tech guys aren't safe.
Wasn't there already a ruling that LLM output is not protected by copyright?
1 reply →
> Advertising requires good user models to work…
…and yet, everywhere I go I see massive advertisements on billboards, the sides of buildings, public transit, movie screens…
3 replies →
I think defaultism plays a huge role. If your wife's next smartphone or TV or whatever comes with AI made by a different company, I think she won't really care and use that if it's good.
By the way this is a perfectly rational stance. If the supermarket next to me stopped stocking Coca Cola, I would just by Pepsi.
The moment openai starts charging for their service properly, people will start shopping around.
See power users such as devs with coding assistants that have model selection dropdowns allowing you to switch on a whim. There is zero loyalty or stickiness in the paying user crowd.
Or using ads
1 reply →
I am starting to believe that OAI might actually succeed at getting per token inference cost to where it needs to be. Or that it's already there in principle.
Wafer scale compute is a very big deal. Most of HN is probably still unaware that you can get tokens out of one of these devices right now via public API offerings.
Not sure how that works when there are fierce competitions, and openai's product is not substantially better than the rest. There are US competitors, then China.
Take ozempic as an example. The word is already part of the culture, but the company is losing badly to lly. Novo nordisk is projecting revenue DECLINE while eli lilly is still growing massively. I am not even sure people know other glp1 drugs other than ozempic. I don't even remember lilly drugs name.
I think people should not underestimate the market. It's a dynamic game where engineering intuition might not be enough
Google is sticky too, and has a huge moat around that access (android, browsers).
Google hasn't yet pushed hard into dominating the chatGPT use case, but they could EASILY push out chatGPT if they tried. For example, if they instantly turned their search page to the gemini chat, they would instantly have dominated openAI use cases. I'm not saying they would do that, they will probably go for the 'everything app' approach slowly
I think the use cases of chatGPT and google are not differentiated enough to justify 2 winners
Netscape had a 90% market share in 1995. If OpenAI is metaphorically netscape, what prevents its competitors from prying away customers every day? What prevents google/facebook/microsoft from using their position to bundle chat experiences? Especially if the tech is a commodity and OpenAI's models are about as good as everyone elses?
In 1995 no one used the web still. Sure, we all did, but it was pretty niche. I think you could argue that chatbots are niche as well, but the user base of OpenAI is way larger now than Netscape in 1995. Netscape had probably 25 million users at the end of 1995. ChatGPT has about 800 million.
I never considered that. When I change LLM models its usually due to two reasons.
1. the current AI model is producing answers that do not met my needs so I try multiple others at the same time and the one that produces the best answer I stick with until I have this problem again.
2. there is a new model released and advertises a new capability that I want to try out.
I can imagine that for many people the answer that ChatGPT generates is adequate enough that they never need to try another model even if better answers exists from another model. For people with less complex needs this is a very real stickiness. Why make the effort to try something new if the answer is adequate.
In this case, OpenAI would only f*k up if they change the pricing significantly, add intrusive ads or their answers become significantly worse.
> The near billion users OpenAI has
They're losing market share and the growth of active user plateaued. They captured all the normies who learned about llms on TV but these people will never spend a cent as you said.
They're not even on the top 10 most used llms on openrouter anymore: https://openrouter.ai/rankings
At the current pace anthropic will make more money than openai soon: https://epochai.substack.com/p/anthropic-could-surpass-opena...
https://menlovc.com/wp-content/uploads/2025/07/2-llm_api_mar...
I’m not rooting for open AI but OpenRouter is a very self selecting group. Most API users of Anthropocic or OpenAi would just go through the normal API
I'm surprised how many of my technical team use free ChatGPT in their personal lives. The rest have Claude subscriptions. I'm the only one with ChatGPT and Claude subs and I'll be switching from Claude Pro to Ckaude Max and cancelling ChatGPT, since I only use it when I hit my Claude quota.
> people have hundreds and thousands on conversation on these apps that can't be easily moved elsewhere
Neither can they be easily searched nor organized. And what prolonged AI use teaches you is: don't search for that old chat, just ask anew.
That particular piece of flypaper isn't as sticky as it may seem.
Switching llms is like switching a car. Its a bit annoying in the beginning, it responds slightly different and you need to change you subconscious habits before it feels comfortable. Why everyone always complains about new models. So unless there is a very obvious improvement; most users will prefer to stick to their current llm
That has not been my experience at all. My mom and dad were able to switch from ChatGPT to Gemini without any friction whatsoever. I myself round robin between Claude, Gemini and ChatGPT all the time.
I disagree. Are people really that attached to their conversations though?
Anecdotally, the vast majority of my own conversations and coding interactions are transient in nature, to the point where I prefer to use the ‘temporary’ mode in whatever tool I’m using.
For coding, every project needs a plan and readme to get whatever agent back up to speed with what the task is. Anyone with a paid-for GH Copilot license knows that you can just switch between whatever provider at a whim, depending on the needs of your task or financial requirements.
I think people will find it easier to revert back to Siri 2.0 if that ever materialises, in which case the stickiness moat is bridged by a more familiar and widely integrated abstraction layer.
I imagine the stickiest customers would be large enterprises. You aren't going to get the evangelists to stick on a single model provider, so their best bet is probably employees who are going to have their choices dictated to them by whoever purchases the softare. (Especially in large enterprises where using an unapproved AI provider is likely not allowed, or the AI is imposed on the workers.) The question then is, how do you differentiate yourself in enterprise sales? As much as people seem to dislike Copilot, from a business standpoint "buy the extra microsoft thing in our current contract" or "buy the extra google thing in our current contract" could likely be a lot cheaper/less friction.
It's really easy to overcome that -- just sponsor some IndieDevs to flood the internet with scripts and tools to migrate all your conversations from OpenAI. Make it easy for people to switch using a simple process, make sure it's well distributed, and BOOM! Watch their user count drop like a rock. People act like just because a service has a lot of users it can't be destroyed. Anyone who has ever worked at a large web company can tell you otherwise. These things can be destroyed in a just a few days if they are targeted.
They look like fortresses from the outside, but they are all incredibly vulnerable. That's the truth they don't want people to know or realize just how vulnerable they all are.
Do people care about their old LLM sessions?
I might have sessions I revisit over a few weeks, but nothing longer than that. The conversations feel as ephemeral as the code produced. Some tiny fractions of it might persist long term, but most of it is already forgotten and replaced by lunch time.
My barber does. It's his therapist and the fact that it knows all about his life is very important to him.
1 reply →
I disagree. So far I've seen people use "Photoshop" and "Google" as verbs. No one uses "ChatGPT" as a verb. People do use ChatGPT but the brand recognition isn't that strong.
My anecdotes are that Google is winning even on consumer side.
As a verb, no, but the product name somehow feels the wrong shape to verb it. I'd say the voice assistants have Google at a disadvantage for similar reasons: "OK Google" is clunky, whereas "Hey Siri," and "Alexa," are not.
But to ChatGPT: when I wander around Berlin, I do overhear people talking about ChatGPT by name.
For all the typical integrated LLM-based "assistants" in other products, I mainly hear people saying things like "I hate it" and "how do I turn this off" and so on, including the one Google has on its search results.
The other pure-play chat-bots that have enough mind-share to even be in the news are Grok (where twitter users seem to like it a lot, even though everyone else up to and including non-US world governments hate it to the point of wanting it banned), Claude (but even then only because of Claude Code), and DeepSeek (because it shows China has no difficulty keeping up with the US). I heard about Mistrial when it was new, but even with the app on my phone I didn't think about it again until about a month ago.
Ask a normal person about Gemini, I'd expect them to think you were talking astrology, not AI.
> No one uses "ChatGPT" as a verb.
In my experience, they do, a lot. "I asked ChatGPT" is something I hear a lot. And yes, this example is not using ChatGPT as a verb, but the idea of brand recognition is there; it's just a grammar thing.
2 replies →
My wife uses Google AI overview - as an extension of search - on a daily basis and then jumps to Gemini
How do you jump to Gemini from AIO? (I know there's AI mode, but it's separate from the Gemini chat product afaik -- except maybe sharing some model lineage)
I don't know. I switched to Gemini and haven't missed anything from OpenAI even for a second. I could switch back to OpenAI and not miss anything from Gemini. I don't feel the stickiness AT ALL.
I don't think they have a billion active users who opted-in. Google/Apple/Microsoft are the gatekeepers (for the most part) for retail users and they decide who is on by default. The USG isn't going to step-in and the EU won't step in either.
So I suspect that Google will lean into Gemini, Microsoft will lean into OpenAI, and Apple ... it's a tough question what they do in the longer term.
For business users it's a different story and I see room for Anthropic to shine. And then there are the specialty AI services but those are all different markets from the general purpose AI.
I think Google may just end up winning on the good enough / cheap enough dimensions as things get more commoditized in LLM world.. in that they can be the lower cost provider given how vertically integrated they would be compared to OpenAI relying on hyperscalers.
1 reply →
> Apple ... it's a tough question what they do in the longer term.
my guess is the just keep licensing gemini and move on with making more money instead of selling 100 year bonds to raise debt.
Just as people underestimate bundling and multiple-product companies. As soon as LLM corpos will start increasing prices to actually match expenses and recouping their immense debts customers will very quickly catch up how OAI product is x5 times more expensive than Google's and the only moat is is to open pre-installed Gemini :) .
Competing in freeware products is impossible as soon as monopoly emerges. Competing in paid products is way easier, especially after free money age has ended.
At this moment, I agree. Your average person (which doesn't really exist) has already been exposed and trained on ChatGPT. Arguing moving to another "chat" experience has not gone well, for example Bing, etc. Pretty sure Google had the "box" figured out first and won. I think people overthink how much effort people are willing to put into "change". There is nothing wrong with staying put if it works, after all, there is an unlimited number of other things happening in this world besides AI.
I definitely think they’ve nailed the personality better than others too. Gemini and grok are always paragraphs and paragraphs of text to sift through for something that with openai is usually digested to much less
To the extent that it is a popularity contest, that's one thing.
Of course the first thing people may look at is technologies going head-to-head.
Another big one is user pricing, plus the underlying cost to serve users. Actually minus that cost.
Biggest so far is capital.
Seems to be going that way, a contest of capital could dominate like so many other things regardless of technologies.
There are probably other things that companies may leverage if competition does really ramp up.
It may not have to be a moat to be a defining characteristic that some prefer.
The difficulty is that “winning” in this case is setting up a monopoly or duopoly and slowly increasing prices. It’s not clear if OpenAI can get so far ahead of the competition that it becomes a two or one horse race. Right now Anthropic and Google are at least as good. And the open source models keep them all honest pricing wise.
OpenAI will likely keep their billion users, and likely monetise them fairly effectively with ads. Their revenue will be considerable. It’s less clear that OpenAI will “win” and their competitors won’t.
My nontechnical friends only know about ChatGPT, all other LLMs are a complete and total mystery to them outside of what is built into Google's search engine and Copilot. I imagine they represent the majority of consumers. It'd require significant marketing campaign for most of them to switch or for OpenAI to make a substantial mistake.
do they use facebook or instagram? meta jammed their LLM into the search box there. Do they use google at all? the AI summary produced by Gemini leads you to click on "more details" with gemini.
so while this is technically true: > My nontechnical friends only know about ChatGPT
they may actually use a ton of other LLMs without knowing
I think there are users who view "their AI" as somewhere in the venn-diagram of their relationships.
And it's a spectrum, at one end you got the full-on AI psychosis and at the other "its a machine, I owe it nothing".
Conversational AI is going to be sticky to the extent that you see a switch to a different provider as dropping a relationship.
I don't really see that stickiness to be honest.
Most people I know with android phones, myself included, just use Gemini which is bundled with the OS and has a dedicated button, has excellent data and integration with maps and such.
When it comes to enterprise, non IT companies (banking, insurance, etc) in Europe seem to be defaulting to Google's offerings, Gemini and NotebookLM in particular.
The problem with the stickiness is that they will eventually need to start charging, and that friction point will immediately make them come undone. Let’s says they charge $1.99 a month, and Anthropic then step in with a six month free offer, and suddenly everyone has two apps on their phone they’re comfortable with, and it’s a price war over very lightly differentiated products
Google has bigger network effect. It can stomp OpenAI
The problem is that, at least for now, it is dead easy to switch to something else. No need to convert anything, reconfigure anything, it is not like changing gmail to something else or dropping Word for LibreOffice.
Chat window is a chat window.
I can imagine that sooner or later things like OpenClaw (or its alikes) will become more popular and that could be something that will catch users.
I disagree (imo).
It would take me minutes to copy across a histories of projects and continue relatively unscathed by the experience.
I use chatGPT and currently relatively like it. But there is no moat beyond that.
Not like, for example, whatssap where it's almost impossible to detach from it due to the network ... (I've really tried with about a 10% success rate)
> I think OpenAI has better chance to winning on the consumer side than everyone else.
Which doesn't make money.
> Of course, would that much up against hundreds of billions of dollars in capex remains to be seen.
Most of that is a bet against enterprise adoption. Automation of customer service, sales, marketing, warehouses, medical discoveries, etc...
Isn't half the appeal of AI that they can write a prompt like move all my text history from OpenAI to Claude and then they do it?
But the (royal) Wife needs to 1) know that exporting is a concept, 2) automating an export is possible, 3) you could ask claude to do it, 4) what an API key is or how to connect services.
My mum, and probably nearly a billion other users, could probably imagine step 1 but not connect to step 2 beyond copy-paste. Most people are still out here sending screen shots of their phones instead of just copying a link or hitting "share" on the image.
But also a billion users is ChatGPT's biggest weakness. So many free users burning compute up. So many incentives to nerf the intelligence to affordable levels. Sounds like a nightmare.
several of my friends named their chatgpt 'Amanda' or 'George' because they talked about real mental issues with it. I don't see them moving to another platform because that's essentially asking them to leave their 'best friend/therapist'.
... your friends should probably see a human therapist before going much further... I don't mean this in a flippant or insulting way.
These articles are largely based on a false equivalence of LLM=moat.
That's not the case. OpenAI is advancing on many fronts; codex, vectorStore, embeddings, response API, containers, batch processing, voice-to-speech, image generation... the list goes on.
by this argument Google will win though. Identical interface with similar quality answers
I wish it would be, but it's not. Gemini feels more sluggish, it's relatively overloaded with animations compared to chatgpt. Like most Google products.
2 replies →
As a counter anecdote, my wife stopped using it because it is quite terrible when you ask it about current events. She almost exclusively uses the Grok app now because it has the "best" internet search and current events results
>the Grok app now because it has the "best" internet search
Why is this? Thanks to Twitter? More aggressive proxy use? Tuned to deliver to stay competitive? …
Was under the impression they didn’t have much in the way of secret sauce.
Exactly. ChatGPT is ubiquitous for the new generation of AI (LLMs) for everyone outside our of bubble. I've spoken to dozens of friends and non-techncial folks about this topic over the last year and not a single one has ever said they use Gemini, Grok or Claude.
OpenAI has by far the strongest brand and user base. It's not even close.
And, when it comes to the product they've been locked in the last few months it seems. The coding models are no longer behind Anthropic's and their general-use chat offering has always been up there at the top.
>on conversation on these apps that can't be easily moved elsewhere.
they can be super easily moved. just use the existing export feature, all a competitor needs is ability to import conversations.
I think you're overestimating stickiness. People spoke endlessly about stickiness of Google for years and years and it took what 18 months for Google search to become virtually irrelevant after LLMs came along?
They are more easily moved than other data honestly. You can use chat gpt to build your own chatbot and then export all of your data from openai and load it into the new chatbot.
Completely disagree with this take. I was an early free OpenAI user and switched to Gemini once it got good enough and bundled a bunch of services together to make the paid product free. OpenAI will need distribution to maintain any kind of durable market share. They need to become a bundler of other subs, or else they will just be the next Disney+ or Spotify that needs telecoms (Hah!) to push their paid product onto user's phone bills.
> but people have hundreds and thousands on conversation on these apps that can't be easily moved elsewhere.
But why would you want to?
You can just leave them there at slowly start new conversation on another platform.
It's way too easy to export your context for this to be real. I moved away from ChatGPT from Gemini months ago and haven't thought of it. Paid.
Conversations are not really a valuable service for these companies. The token usage is miniscule.
Agentic development and claw style personal assistants are where the dough is at.
At the conversation backlogs worth anything? To me they seem as valuable as Google search history. After maybe 3 days they are worthless.
People get attached to month long conversations, strangely. Sometimes even refusing to use the fork feature.
And the memories are also something that adds to this greatly.
1 reply →
All of ChatGPT's users could be gone in a month if something better comes along. And plenty of other options are coming along.
This obstacle looks familiar.
Having a known brand is not a moat mate. Sorry.
myspace used to be a well known brand. I've worked there.
i've been using chat gpt for 'chatting/questions' kind of things + snippets of code
it's plenty good on free tier
as soon as they start adding restrictions / raising prices / etc won't take long to look for alternatives
A good solution for memory would help with stickiness. But it's a hard thing to crack.
We are in the Yahoo, Altavista, Lycos etc. stage. Plenty of room for a Google still.
> Everyone is actually underestimating stickiness. The near billion users OpenAI has is actually a real moat and might translate into decent chunk of revenue.
Maybe you're overestimating their "moat" and stickiness. The dust is still settling on this madness and "OpenAI"[1] creates a lot of noise in the market.
These LLMs are being rapidly commoditized, very soon they will become as "boring" as virtual machines or containers. Altman has the exceptional skill to dupe people into giving their money to him. The "infinite money glitch" that he has been exploiting isn't really infinite.
I just hope there'll be a breakthrough with truly transparent LLMs that will stabilize this madness. As I've griped[2] two years ago, I find OpenAI too scummy, and it is unlikely that they will "win" with their sleazy ways.
[1] Air quotes because of their persistent abuse of the word "open"
[2] https://news.ycombinator.com/item?id=40425735
nah, open ai doesn't have a moat it has a brief window to get a lot cheaper to run or it's going to go pop when someone figure out how to do inference a lot cheaper.
How much is your wife paying for the privilege to use OAI presently?
This is the real question. Is she willing to pay $20 per month when Google's Gemini is free? Google can remain irrational longer than OAI can remain solvent.
6 replies →
Does she pay for it. No? Then she’s causing them a loss
This is what Netscape thought too
I really like your analysis and agree up to a point.
The problem with a moat in the consumer space is it depends on brand and marketing. OpenAI came into this world as a tech novelty, then an amazing tech tool, then a household name.
But… can they compete with massive consumer companies like Apple, Google, etc? In the long run?
There’s no technical reason they can’t. The question is whether they have consumer marketing in their blood. The space doesn’t have a lot of network effects, so it’s not like early Facebook where you had to be on it because everyone was.
Not saying they’ll fail, just saying it would be a significant challenge to be a hybrid frontier model / consumer product company.
And?
The tech landscape is littered with companies they had users who couldn’t monetize through ads. Beside the costs of serving request via LLMs is orders of magnitude greater than a search result.
On top of that, OpenAI is a sharecropper on other companies’ server, they depend on another company’s search engine and unlike Google, they are dependent on Nvidia.
Don’t forget that most browsing is done on the web and Google is the default search engine on almost every phone sold outside of China.
That being said: I used MySpace daily too... Until I didn't.
OpenAI got me to cancel my anthropic sub for Codex. Anthropic weekly limits on Pro are atrocious. You listening anthropic?
Microsoft is surviving precisely because of stickiness as you put it. But their users have to use them, and have to pay for it. There are very few people that use openai today that have to pay for it, those forced to use it are typically doing so via free avenues like windows copilot.
OpenAI has the stickiness of MSN news or MS Teams. Your wife uses chatgpt on a daily basis but is she paying for it? If they charge her $0.99/mo will she not look at alternatives? If she gets two or three bad responses from chatgpt in a row, will she not explore alternatives to see if there is something better? Does she not use google? If she does, she is already interacting with gemini everyday via their AI overview.
OpenAI has a first-to-market advantage, not a moat as you think. they can absolutley dominate the market, if they stay on top of their game. Ebay was the main online shopping network, they had that advantage, they were even the ones that made Paypal a thing! But they're relatively little used now, better alternatives crushed them.
Amazon was the first-to-market with cloud services, they didn't get worse in any significant way, but their market share is not as great as it used to be, Azure has gained decent ground on them. 10 years ago the market share break down was 31/7/4, now it is 28/21/14 for AWS/Azure/GCP respectively.
For OpenAI to survive it needs most of the market share, if it gets only a 3rd for example, the AI industry on its own needs to be a $1T+ industry. Over the past 10 years revenue alone (not profit) for AWS has been $620B total and just made $128B in revenue (highest) last year. OpenAI needs to make in profits (not revenue) what AWS made last year in revenue by 2029 just to break even. If it manages to just break even by then, it needs to have more profits than the revenue AWS managed to attain after its entire lifetime until now. It's far easier to switch LLM models than cloud providers too!
Their only remote way of survival, I hate to say it, is by going the way of palantir and doing dirty things for governments and militaries. they need a cash-cow client that can't get anyone else like that. And even then, being US-based, I don't think outside the US any military is insane enough to use OpenAI at all due to geopolitics. Even in sectors like education, Google (via chromebooks) is more likely to form dependence than Microsoft via OpenAI since somehow they're more open to arbitrary apps due to historical anti-trust suits.
I can see a somewhat far-fetched argument being made for their survival, but only on thin-threads and excellent execution. But I can't see how they can actually survive competition. They're using the Azure strategy for market share, they're banking on AI being so ubiquitous that existing vendor-lock-in mindset will serve as a moat. They'll need to be much more profitable than AWS in like 1/5th of the time. Their product is comparable to (and literally is in Azure) one of many cloud service offerings, as oppose to an entire cloud provider, and their costs are huge similar to cloud providers like needing their own data-centers level huge, they need to overcome those costs, and on top of that have $125B> revenue in like 2 years!!
I have started using chatgpt for everything from financial planning to holiday planning to product purchase. Whenever I think I hit something useful I add it to memory. I'm a "go" plan user because they had a promotional offer that gave me free access to the plan for a year. Will I continue after one year? Truth is nothing I have in chatgpt cannot be recreated elsewhere. But if I care about keeping those memories I might. I think the real challenge for me now is finding back out conversations, it seems their history search is quite bad.
Yup this is just another case of the HN bubble. I polled a bunch of non technical friends recently who I know use AI on a daily basis. Out of 10+ maybe 2 had ever heard of Claude, and no one had any interest in trying it.
ChapGPT has become the AI verb, and in the consumer space it is not getting dethroned.
Claude is definitely tech only.
Gemini is the only real competitor to OpenAI in the consumer space: they already have the consumer eyes on their products and they have the financials to operate at a loss for years.
They are well positioned to fight for the market
I just wonder how long it'll take local models to be good enough for 99% of use cases. It seems like it has to happen sooner or later.
My hunch is that in five years we'll look back and see current OpenAI as something like a 1970's VAX system. Once PCs could do most of what they could, nobody wanted a VAX anymore. I have a hard time imagining that all the big players today will survive that shift. (And if that particular shift doesn't materialize, it's so early in the game; some other equally disruptive thing will.)
In my experience with Gemini, most of its capabilities stem from web searching instead of something it has already "learned." Even if you could obtain the model weights and run them locally, the quality of the output would likely drop significantly without that live data.
To really have local LLMs become "good enough for 99% of use cases," we are essentially dependent on Google's blessing to provide APIs for our local models. I don't think they have any interest in doing so.
I agree 100%. Often when I use increasingly powerful local models (qwen3.5:32b I love you) I mix in web search using search APIs from Brave, Perplexity, and DuckDuckGo summaries. Of course this requires that I use local models via small Python or Lisp scripts I write. I pay for the Lumo+ private chat service and it has excellent integrated search, like Gemini or ChatGPT.
EDIT: I have also experimented with creating a local search index for the common tech web sites I get information from - this is a pain in the ass to maintain, but offers very low latency to add search context for local model use. This is most useful with very small and fast local models so the whole experience is low latency.
3 replies →
That's totally not my experience. The AI component (as opposed to the knowledge component) is really what makes these models useful, and you could add search as a tool. Of course for that you'll be dependent on a search provider, that's true.
3 replies →
This is actually so ironic. Corporations spent fortunes to design cool websites, but what people really want is structured, easy to read information in the context they want.
So flow is you type search query to Gemini, Gemini uses Google search, scans few results, go to selected websites, see if there is anything relevant and then compose it into something structured, readable and easy to ingest.
It's almost like going back to 90s browsing through forums, but this time Gemini is generating equivalent of forum posts "on the fly".
1 reply →
Unless you can provide a (community) curated list of sources to search through (e.g. using MCP). Then I think local models may become really competitive.
Taking the opposite side of that bet, here is why:
* even if an openweight model appears on huggingface today, exceeding SOTA, given my extensive experience with a wide variety of model sizes, I would find it highly surprising the "99% of use cases" could be expressed in <100B model.
* Meanwhile: I pulled claude to look into consumer GPU VRAM growth rates, median consumer VRAM went 1-2GB @ 2015 to ~8GB @ 2026, rougly doubles every 5 years; top-end isn't much better, just ahead 2 cycles.
* Putting aside current ram sourcing issues, it seems very unlikely even high-end prosumers will routinely have >100GB VRAM (=ability to run quantized SOTA 100b model) before ~2035-2040.
Even with inflated RAM prices, you can buy a Strix Halo Mini PC with 128GB unified memory right now for less than 2k. It will run gpt-oss-120b (59 GB) at an acceptable 45+ tokens per second: https://github.com/lhl/strix-halo-testing?tab=readme-ov-file...
I also believe that it should eventually be possible to train a model with somewhat persistent mixture of experts, so you only have to load different experts every few tokens. This will enable streaming experts from NVMe SSDs, so you can run state of the art models at interactive speeds with very little VRAM as long as they fit on your disk.
3 replies →
There will be companies producing ICs for cheap models, like Taalas or Axelera.ai today. These models will not be as good as the SOTA models, but because they are so fast, in a multi-agent approach with internet/database connectivity they can be as good as SOTA models, at least for the general public.
3 replies →
The GPU makers have been purposely stunting VRAM growth for years to not undercut their enterprise offerings.
yeah but effective GPU RAM has ramped thanks to unified mem on apple. The 5y thing doesn't hold anymore.
I agree, but I'm holding out hope that ASICs, unified RAM, and/or enterprise to consumer trickle-down will outpace consumer GPU VRAM growth rates.
Increasing model size doesn't make your model smarter, it just makes it know more facts.
There's easier ways to do that.
The trend with email, websites and so on has been to use some large cloud service rather than self host as it's easier. My bet is AI will be similar.
You can turn a local model on and off as needed, and it will still function as expected. If you turn off your self-hosted server, you don't get email.
With self-hosted email, you need persistent infrastructure and domain knowledge to leverage it. With a local model, you just click a button and tell it what to do.
With email, there is a necessary burden to outsource. Your local model is just there like Chrome/Edge/Safari is just there, there is no burden.
But AI is not about connectivity. Local models are just about as useful without an internet connection. Also, the hardware can fit in a small enclosure.
5 years is a bit optimistic. I have no desire to use anything dumber than Claude - but I doubt I'll need something much smarter either - or with so much niche knowledge baked in. The harness will take care of much. Faster would be nicer though.
That still requires a pretty large chip, and those will be selling at an insane premium for at least a few more years before a real consumer product can try their hand at it.
Coding, via something like Claude or Codex, will likely always be something best done by hosted cloud models simply because the bar there can always be higher. But it's already entirely possible to run local models for chat and research and basic document creation that can compete perfectly fine with the cloud models from 6 months to a year ago. The limitation at this point is just the cost of RAM.
This week's released of the new smaller Qwen 3.5 models was interesting. I ran a 4-bit quant of the 122b model on my NVIDIA Spark, and it's... pretty damn smart. The smaller models can be run at 8-bits on machines at very reasonable speeds. And they're not stupid. They're smarter than "ChatGPT" was a year or so ago.
AMD Strix Halo machines with 128GB of RAM can already be bought off the shelf for not-insane prices that can run these just fine. Same with M-series Macs.
Once the supply shocks make their way through the system I could see a scenario where it's possible that every consumer Mac or Windows install just comes with a 30B param or even higher model onboard that is smart enough for basic conversation and assistance, and is equipped with good tool use skills.
I just don't see a moat for OpenAI or Anthropic beyond specialized applications (like software development, CAD, etc). For long-tail consumer things? I don't see it.
1 reply →
Yeah, post-Moore's Law anyway. But there could also be real breakthroughs in model architecture. Maybe something replaces transformer with better than quadratic scaling, or MoE lets smaller models and agent farms compete, or, who knows....
I hope you're right, but is there any guarantee that there will continue to be institutions willing to spend the money to produce open models?
I almost wonder if we need some sort of co-op for training and another for hosted inference
There doesn't seem to be any sign of Chinese companies stopping to produce open models to destroy the American moat.
Given that a lot of the R&D in China is state sponsored that also seems to be a good pawn in US-China relations.
1 reply →
Think a large portion of people won’t take “good enough” if better is available for cheaper.
Datacenters simply scale better than homesevers on cost and performance
So only really works for people that value local highly - which isn’t most people.
Why would we assume the remote providers are going to be cheaper? They are burning cash, and Claude is already jacking up prices.
"Local" is the means to an end, not the value prop itself. The value prop is "fast, private, and free", which I think is going to be very compelling.
> I just wonder how long it'll take local models to be good enough for 99% of use cases.
Qwen 2.5 was already there. "99% of use cases" isn't a very high bar right now.
Yesterday I asked mistral to list five mammals that don't have "e" in their name. Number three was "otter" and number five was "camel".
phi4-mini-reasoning took the same prompt and bailed out because (at least according to its trace) it interpreted it as meaning "can't have a, e, i, o, or u in the name".
Local is the only inference paradigm I'm interested in, but these things have a way to go.
I don't really see the problem here. Yeah, we know that these models are not good for actual logic. These models are lossy data compression and most-likely-responses-from-internet-forums-and-articles machines.
This kind of parlor tricks are not interesting and just because a model can list animals with or without some letters in their names doesn't mean anything especially since it isn't like the model "thinks" in English it just gives you the answer after translating it to English.
These are funny, like how you can do weird stuff with JavaScript language by combining special characters, but that doesn't really mean anything in the grand scheme of things. Like JavaScript these models despite their specific flaws still continue to deliver value to people using them.
7 replies →
Models will always struggle with this specific task without tool use, because of the way they tokenize things. I think a bit of prompt engineering, asking it to spell out each work or giving it the ability to run a “contains e” python function on a lot of animal names it generates or searches for solves this.
Lots of local ai use cases I think are solvable similarly once local models get good at tool use and have the proper harness.
2 replies →
Treat LLMs as dyslexic when it comes to spelling. Assess their strengths and weaknesses accordingly.
4 replies →
Convenience trumps everything, including privacy and security.
Tell the average person that they have to install their own model is a deal breaker at the outset.
As for 99% capabilities being on device, battery life makes it a non starter.
My conspiracy theory is oai saw the writing on the wall and the massive gpu commit was in part to starve the market to delay this inevitability.
I think this is the best article on open AI that I've ever read. A lot of content these days will try to paint OpenAI in sensational ways that really doesn't get to the bottom of whether open AI has an economic mode, and this article does a very thorough job of explaining why OpenAI doesn't have power like the other platforms.
And so this goes back to my theory that open AI's execution is basically to get it itself in a position where the market cannot afford to have it implode. Basically, it wants to or it needs to be too big to fail. And I think we're already kind of seeing the politicization, if you will, sort of the rocket race between two superpowers or large powers on the AI front, and I think that Might be a viable strategy.
I don't see OpenAI being too big to fail happening, the public is already very skeptical of AI. Also, there are other options available and therefore not a national security issue. Finally, OpenAI failing has no impact on employment or like societal disruption. In fact, it may increase employment if OpenAI fails.
The only other way to reach too big too fail status is if allied countries risk collapse if it goes under ( like the big banks in the financial crisis ) which I don't see happening either.
Yeah, I was a bit surprised that the author didn't mention that facet of Open AI. It did mention infrastructure goals, but the reality is that Open AI's infrastructure spending commitments have inflated the stock prices of quite a few hardware companies (like Micron and WD) and caused a strain on the market.
The real danger here is how over-leveraged Open AI is. No other AI player is as exposed. Their massive spending commitments are all precariously balanced on the other end by their user base, and if that evaporates, the whole thing will fall apart and that could crash the stocks of other players ...and by crash, I mean bring them down to a realistic value. But the economy is counting on this to work, which is why I believe that Open AI's strategy here really is to make the market exposed to Open AI's risks.
Altman said that in an interview, that the government would bail out OpenAI.
does anyone have a citation/reference for this?
Hopefully this is on-topic: I would hope that some people would opt for private chat services. I evaluated both Proton’s Lumo+ and DuckDuckGo’s Duck.ai services. I like both services but only wanted to pay for one and I chose Lumo+ because chat history is stored with my Proton data and is available in all my devices, Duck.ai stores chat history on current access device. Both services are also very usable with their free plans.
At least some of us in HN talk about limiting the data we give to Facebook, Google, Microsoft, etc. Isn’t it just as important to limit what we share with non-privacy preserving AIs?
Note: tech friends have asked me how I can use slightly weaker AI models and be happy about it: I still use Gemini Plus (and Anthropic via AntiGravity) for technical work: everything I do as a software developer is open source and all of my writing (20+ books) is Open Content so I don’t care about privacy and being direct-marketed based on my tech work. To me it makes sense to use the best AI just for tech work and a private AI for everything else. Think about this if a family member has a serious health problem, or something else private: do you want to use open web searches and open AI chats, or do you want to use private web search and private AI access? Why not make privacy your default, except in special situations?
> DuckDuckGo's Duck.ai services ... what we share with non-privacy preserving AIs.
Duck.ai's Privacy Policy goes:
This is not much different to the BigLabs, tbh.
Otoh, privatemode.ai, confer.to, trymaple.ai are at least attempting Apple AI-like confidentiality.
That's a fair point, but DuckDuckGo has been a privacy champion for years, so I would give them far more weight in actually adhering to these policies as a middle-man than to directly trust the others. The priorities are different.
I have a family member with a serious health problem, and I've been using Claude code to put together a very comprehensive medical dossier.
I'm not worried about the privacy aspect though many suggest that I should be. The power the dossier has given them to navigate the medical industry in the United States has been absolutely incredible. They don't have to be stuck when a random doctor who has never heard of their illness suggests that they might be overreacting. They can simply find someone who will help them. They can talk, in medical lingo, about their test results and discuss them with the doctor on equal footing.
I'm not sure this would've been nearly as successful without Opus 4.5/4.6 driving the harness. I'm not also not sure what real privacy risk there is here; it all sounds very theoretical.
There are also encrypted AI chatbots like Tinfoil and Confer that E2E encrypt all data to a secure hardware enclave. I also use Claude and OpenAI for non-privacy needing tasks, but use Kimi-k2 on tinfoil when I need privacy. Kimi-k2 feels close enough to SOTA so I'm happy with it.
I think this take underestimates a couple points:
1) the opportunities for vertical integration are huge. Anthropic originally said they didn’t want to build IDEs, then realized the pivot to Claude Code was available to them. Likewise when one of these companies can gobble up Legal, Medical, etc why would they let companies like Harvey capture the margins?
2) oss models are 6-12 months behind the frontier because of distillation. If labs close their models the gap will widen. Once vertical integration kicks off, the distillation cost becomes higher, and the benefit of opening up generic APIs becomes lower.
I can imagine worlds where things don’t turn out this way, but I think folks are generally underrating the possibilities here.
If OSS models are 6-12 months behind, it means sometime during 2026, we'll see a model that is on par with the likes of GPT 5.2/Opus 4.5.
For code generation specifically, the performance level of this is going to be more than enough for this customer base. What does Anthropic do then to justify $200/mo price sticker? Better model? Just how much better? Better tools? Single company can't compete with the tools entire OSS can produce.
I would be unable to sleep if I was running OAI / Anthropic.
If capabilities stop increasing for some reason, then yeah, Anthropic is screwed.
If METR task times double twice into the multi-day range in 12 months, then it’s plausible to me that Anthropic can charge $1k/mo or more by automating large chunks of the SWE role. (They have 10x’d their revenue every year, perhaps “value of enterprise contracts” is a better way of intuiting their growth rather than “$/seat” since each seat gets way more productive in this world-branch.)
Just game the benchmarks, bro. (The singularity we didn't want or ask for.)
It's what the current model providers are doing anyways.
The question is always about performance plateau. If LLM performance plateaus, then OSS models will catch up. If there isn’t a plateau, then I can simply ask the super intelligent AI to distill itself, or tell me how to build a clone.
It’s ironic, if the promise of AGI were realized, all knowledge companies, including AI companies, become worthless
> I can simply ask the super intelligent AI to distill itself,
I notice I am quite confused by this point. Why would you expect a super-intelligent AGI to honor your request, which would be at least a request to breach your contract with the AI provider, if not considered actively dangerous by the AI itself?
The smarter the AI, the less likely you should expect to be able to steal from it.
> or tell me how to build a clone
Step one: acquire a $100b datacenter. Step 2: acquire a $100b private dataset Step 3: here is the code you’d use to train Me2.0.
I don’t think this knowledge helps in the way you think it does.
1 reply →
I actually think that plateauing is the best case scenario for big labs.
I think there are three broad scenarios to consider:
- Super-intelligence is achieved. In this scenario the economics totally break down, but even ignoring that, it’s hard to imagine that there are any winners except for the the singular lab that gets here first.
- Scaling laws hold up and models continue to get better, but we never see any sort of “takeoff”. In this scenario, models continue to become stale after mere months and labs have to spend enormous amounts of money to stay competitive.
- Model raw capabilities plateau. In this scenario open source will catch up, but labs will have the opportunity to invest in specific verticals.
I believe that we’re already seeing the third scenario play out, but time will tell.
2 replies →
LLM performance has already plateaued. I don't know, nor care what benchmarks are saying, because they not once translated to the real world for me.
The only thing that has seen massive boost are harnesses around AI. And AI companies are behind here compared to OSS.
5 replies →
You are assuming that superintelligent AI will follow every command of users outside the labs.
1 reply →
Not if they can leverage their superior abundance of compute/intelligence to invade other industries.
To go vertical they’d need to illustrate the value-add, a problem that the vertical competitors already have. Why use Claude for Accountants at $300/month when regular Claude will do the same thing for much less? The stock answer is that Claude for Accountants keeps your data more secure and doesn’t train on it. But a) I think the enterprise consumer is much less likely to trust a model creator not to stick its hand in the cookie jar than a middleman who needs the trust to survive, and b) the vertical competitors typically don’t use the absolute most up-to-date models in their products anyway, so why not just go open-source and run everything in-house? 6 months is a long time in tech, but it’s the blink of an eye in most white-collar professions.
Once the majority of work at a company can be done by AI, Anthropic has an alternative revenue stream to selling AIs to that company--directly competing with that company with a completely integrated AI system. There's of course many barriers to entry/various advantages of incumbents--but it's possible to see a world in which the company selling the AI has a huge advantage too.
The point is that in this hypothetical you can get public access to Claude Opus 6, but they internally use Claude Opus 7 (Accounting Finetune) which is both cheaper to operate and higher IQ.
So they (or their wholly owned subsidiary) can sell accounting services cheaper than anyone on the outside.
Regarding the diffusion/distillation time, I assume it gets harder to distill in the world where frontier labs don’t give API access to their newest models.
BTW the distillation (or accusations of it) seems to go both ways. I've seen multiple reports of people asking Claude what model it is -- in Chinese -- and having it answer that it's DeepSeek.
They're all scavengers, and we're the road kill.
I think it’s very plausible that the OSS models are being distilled too, but note that it’s asymmetrical.
You can’t get an Opus 4.5 by distilling from DeepSeek. What you might be able to get is a slightly more cost-effective training data generation pipeline, or something along those lines.
In the other direction, my belief is that DeepSeek could not have been trained without distilling from US labs. They simply didn’t have the compute to do the pre-training required.
Tech has been trying to "gobble up" legal, medical, etc for decades. I'm quite skeptical a newcomer with a powerful model will be able to penetrate them, especially while selling those incumbents access to the same models they are building on.
> Tech has been trying to "gobble up" legal, medical, etc for decades
This time it’s different, obviously.
> especially while selling those incumbents access to the same models they are building on.
In the extreme, i think it’s plausible that frontier labs basically stop selling any access to their leading models. Whatever you make available by API will just get distilled. In the vertical integration world, the only way you get access to these models is by contracting with a company to buy a product (requirements in, code/decisions out) rather than direct conversation with the AI.
I don’t think they would unship Opus 4.6, but there isn’t a strong incentive to compete on chatbot intelligence in this world.
After trying out Pi, I really don't know what 'vertical integration' Claude Code offers. And Pi isn't even the most popular alternative (I think it's OpenCode rn).
Take a look at Harvey. Pi / Opus alone cannot do what this product does.
You can think of this most simply as “model + scaffolding/skills = product”.
As far as I can tell Google Gemini has the best overall integrations (Android, WearOS, Google Home) with the only voice recognition that actually works (Gemini Live).
Anthropic Claude has the best integrations with coding; what would make sense is for them to focus on that segment.
Other AI companies don't have anything really compelling. Meta has a model that's fully open-source, but then that's not particularly useful outside of helping them remain somewhat relevant, but not market-leading.
If you haven’t used codex with gpt-5.3-codex (high or xhigh) you are missing out. Claude is still good at conversations but boy I can have codex go at a problem and it does better than Claude almost all the time. Front end and product UX Claude is slightly better but given the very very generous limits of codex, they are the best bang for buck
this is my experience as well, just cancelled my claude subscription as I'm tired of it the 5 hour window being filled up within 30 minutes of use, and not even fixing the problem that codex finds almost immediately. also found for frontend that gemini 3.1 pro is better than the rest if you really play with it.
1 reply →
Has it been sped up at all? Last time I used codex (which was with 5.1 I think), it was pretty slow. I mean, it did a fantastic job at figuring out hard bugs across multiple languages ("why is this image not lining up in this server-rendered template?"; Python, JS, CSS, and the template lang) but it took quite a long time. Long enough that I wouldn't want to use it for anything but the most complex things.
1 reply →
Absolutely this. Codex right now is the superior coding model.
The tide seems to be shifting on codex, but also lets not forget openai has a brand that none of the others have - it's _the_ AI.
Sure Google can go against that, but it's openai is definitely in a much better spot. It's pretty important for a consumer market.
This thing about openai brand is changing fast. In the dev circles I'm part of, everybody dislikes OpenAI and prefer Claude. How long it'll take for the same to happen with the normies?
2 replies →
The thing is though, Google Gemini is pretty good and it's not super hard to switch to and, the real moat, Google can just keep improving, integrating Gemini, and gathering customer while just waiting for OpenAI to go bankrupt. Basically, everyone on the planet has to pay OpenAI to keep them in business. If they don't get the vast majority of the market OpenAI can't pay their bills. Google is going to just starve OpenAI out.
> Anthropic Claude has the best integrations with coding; what would make sense is for them to focus on that segment.
the problem with coding is the value is really in the harness and orchestration both of which are accessible to the opensource community. ClaudeCode isn't that big of a deal unless Anthropic makes it so that you can only access the models that ClaudeCode uses through ClaudeCode. If not, then projects like pi and opencode have the advantage in the long run. Also, these harnesses being node modules (of all things) make them very easy to reverse engineer with the help of... claudecode ironically.
I’m not sure. I started using Codex last week. Codex, at $20/mo is a very good value.
Indeed! For now let's enjoy it as much as we can. The VC-subsidized price of $20 won't last eternally I'm afraid
> Anthropic Claude has the best integrations with coding
Disagree, Codex is neck and neck with A/ on coding front
Model available != open source
I speak native English and barebones high school Spanish. I recently visited Costa Rica and almost every time there was a language barrier issue (unknown word or phrase), the local folks opened ChatGPT, said what they were trying to say in Spanish and then had ChatGPT convert it to English. It was everywhere.
A cool use case; you can tell ChatGPT voice to act as a translator. When they speak Spanish, translate it to English. When you speak English, translate it to Spanish.
Works pretty good.
> said what they were trying to say in Spanish and then had ChatGPT convert it to English. It was everywhere.
i'm just so surprised they'd use chatgpt to do this, when it's quite as easily (and perhaps faster) to use google translate.
I've had better experience with LLMs translating than any bespoke translation tool, oddly enough. LLMs seemingly have a very good handle on regional varieties. As an example, I've never found a good translator for Lebanese/Syrian Arabic dialects, but ChatGPT was able to easily translate for me, even getting right some lesser used rural accent quirks which I didn't even know how to translate (similar to something like "y'all" in english).
To be fair, I wasn't using it in the way the parent comment described, for me I said: "this person speaking Lebanese/Syrian Arabic said something that sounded like [try my best to replicate the sentence]. What did they most likely mean?" and got a pretty much spot-on answer.
I wonder if this ability translates to other languages, but I wouldn't be able to tell. My Arabic is "good enough" to tell that the translations I got were good, but I'd be interested to here from someone who knows more if, for example fuzhounese translation is any good.
> i'm just so surprised they'd use chatgpt to do this, when it's quite as easily (and perhaps faster) to use google translate.
https://arxiv.org/abs/1706.03762
When OpenAI starts requiring a payment, or showing an ad before it starts translating, will they continue? Or will they use the Google Translate app, which can do this locally? (Or for that matter Gemini or Grok or whatever?)
> showing an ad before it starts translating, will they continue
Yes. What evidence do we have that mass consumers decamp because of ads?
1 reply →
“When Netflix starts showing ads who on earth will still use it?”
Everyone, it turns out. Same with Google. Same with YouTube. Same with Instagram, and the rest of the web.
Once people become dependent on ChatGPT (as they already are) watching a 30 second ad in the middle of a session will become second nature.
2 replies →
Google Translate has been doing this forever and people in countries like Turkiye have been using it for a while. The usecase you're talking about is not exactly an LLM use case tbh.
And yet people are using it for that, even if it's not rational. I use ChatGPT for some things that would be easier and better to do with other tools out of habit.
It's incredible that google translate had this moat for a decade (maybe more) including live translation but people prefer to use chatgpt now
Google translate is nowhere close to as good as AI translate.
5 replies →
I have done that at my home. My wife calls maids. They are there. I need to go to restroom. Ask my wife. She is struggling to communicate. It took me 3 seconds to realize ChatGPT could help. And it did.
Nice that ChatGPT does that, its also true that Google Translate and other APPs have had this functionality for a decade or more. I was getting live German translated on my phone in 2015 with no problems.
3 replies →
These sorts of doom articles are interesting in that they are from the perspective of tech company valuations. Why is this the important perspective?
For the humanity perspective, this doom is very optimistic. It says that these LLMs currently disrupting the platforms cannot themselves be the next platforms.
Maybe no one will have 'the ability to make people do something that they don't want to do' sort of power with this next stage in computing.
Sounds good to me.
These very valid points apply to all companies trying to make money off of proprietary models, which means margins are going to collapse in a vicious price war that will make Uber vs Lyft seem tame.
As margins collapse capex will collapse. Unfortunately valuations have become so tied to AI hype any reduction in capex will signal maybe the hype has gotten ahead of itself, meaning valuations have gotten ahead of themselves. So capex keeps escalating.
None of this takes into account the hoarding effects at play with regards to GPU acquisition. It's really a dangerous situation the industry is caught in.
Couple of observations:
Companies use to hoard talent. Now they are hoarding compute, RAM, and GPUs.
Deepseek showed that there are possibly less expensive ways to train, meaning the future eye watering expenses may not happen.
Bigger models may not scale. The future may be federations of smaller expert models. Chat GPTX doesn’t need to know everything about mental health, it just needs to recognize the the Sigmund von Shrink mental health model needs to answer some of my questions.
Echoing the other comment they showed another big thing which is that the output if an AI model is the AI model. If you mass prompt scrape their AI you can recreate it almost exactly.
Very dangerous if you think about it that the product itself is the raw building block for itself.
Openai spends 1B$ on their model, releases it and instantly it gets scrapped by a million bots to build some country or company their own model.
Deepseek showed that distillation is possible. Their results are possible without someone else doing the leading edge training
Well there's the whole race to ASI thing. Whoever gets there first, the world is theirs. The thing will learn how learn, an intelligence feedback loop, make its own apps, find more efficient algorithms, deploy itself to more locations, bankrupt all competitors, embed itself in everyone's lives, and create a complete monopoly for the parent company that can never be touched. Until it goes rogue anyway.
(Aside, it's interesting how perceptions of these things have changed in one year: a whole article on OpenAI's future that makes no mention of AGI/ASI)
Because it's a fantasy for an unknown amount of time. 1 year? 10? 50? Never? There hasn't been a single proper breakthrough in continual learning that would enable it. Anyone that studies CL will also get super pissed at it the problem and solution counteract each other to our current understanding but a fruit fly does it no problem!
Seems like anthropic is the only company that really believes in AGI still, considering their neglect of the consumer market and continued worries about AI ethics
I don't think "believes in" is the right choice of words. It's more like "can't rule the future possibility completely out so we should at least take some precautions", which seems entirely reasonable and it's a shame not all of these companies are doing so.
ASI still runs at finite speed and is limited by its hardware, and speed of its interactions with the real world. It won’t be able to recursively improve itself overnight if it only generates 10 tokens per seconds, and a second company could very well train one of its own before the first one has time to do much.
You're not thinking of the second order meta system here. ASI isn't just one instance of an LLM responding to you in a session. It's the datacenter full of millions of LLM interacting with millions in parallel.
1 reply →
Why will it do all these things?
Many people say we’re at AGI already and I’m wondering why everyone hasn’t died yet.
> Many people say we’re at AGI already and I’m wondering why everyone hasn’t died yet.
That’s like saying “many people say the Earth is flat and I’m wondering why anyone hasn’t fallen off the edge yet”.
“Many people say” doesn’t translate to reality. Maybe AGI will kill us all, maybe it won’t (I think we’re doing a fine job of that ourselves, no need for a machine’s help), but we’re definitely not at AGI, except in the minds of a few deluded people (or scammers).
4 replies →
> Whoever gets there first, the world is theirs.
Yes, just like the first person who will invent perpetual motion. /s
PS: to be clear, I'm not saying it's impossible but so far, just like perpetual motion or the Fountain of Youth it's an exciting idea anybody can easily understand yet nobody solved since it's been phrased out. It's not a solved problem and assuming it suddenly is is simply a (marketing) lie.
I think the threshold is way below self improve at 0.1% per day. I wonder what is it? At 0.1% is already going to eat the world a couple of months I think
1 reply →
I've churned off OAI in favor of maxing out Claude. Better coding model and less creepy engagement hacking in the chat interface.
I get plenty of creepy engagement hacking with claude’s chat too now. Before memory it was better.
You can always turn it off
3 replies →
Ever since OpenAI stuck the "Memory almost full" ad banner at the bottom of every chat, I've moved away from them. I have Grok in my car, Alexa+ on my alexas, Gemini Plus from my Google Workspace account, Microsoft Copilot at work, Claude Code because I like it, Opencode because it's free enough -- by spreading my chats around I'm not beholden to any single of them.
None of these can't be moved away from immediately. Even with my github repos, I use Antigravity, Claude Code, Opencode, and I might try Codex. I use one of them as a primary more than the other, but they're as close to interchangeable as possible.
If Codex 6.0 is better than Opus 4.9, things will flip. While OpenAI has too many common enemies and trying to box them into a consumer company, they are equally enterprise focused. They need to absolutely do well with foundation model - everything else depends on that.
Well, codex is better than opus right now. I have both subscriptions, and use claude for grunt work + codex for reviews. Codex is comparable at code writing but does much better with tools, skills and ad hoc investigations, say, lauching emacs and inspecting internal emacs state on the go.
Same, I also have both subscriptions (100 Max and 200 Pro), and I am considering canceling MAX plan but would give it another month on watch.
The doomer sentiment is quite baffling to me, what trouble is OpenAI in? Definitely not after GPT 5.3. They have the model and they have the compute, people just don't realize it yet.
Might be I am in a twitter bubble, most people seem already team Codex
I keep hearing about how the app integrations will be where the AI value is and then I see the actual app integrations and they are between useless and mildly helpful.
From what I can see Anthropic's big bet is that they will solve computer use and be able to act as an autonomous agent. Not so sure how fast they will progress on that. OpenAI on the other hand - I have no idea what they are planning - all I'm reading is AI porn and ads.
Google seems to be lackluster at executing with Gemini but they are in the best position to win this whole thing - they have so much data (index of the web, youtube, maps) and so many ways to capitalize on the models - it's honestly shocking how bad they are at creating/monetizing AI products.
Google is doing a much better job integrating AI into existing products. Gemini CLI and such seem just like a way to keep the leading competitors humble (a la iOS vs android). They're also building AI tooling tailored to specific companies (like the Goldman thing just announced) and have the cloud infra to back it up. I really only see Anthropic and Google surviving in 10 years.
Ai porn and ads may be a bigger market than anthropics b2b
OpenRouter top apps are 50/50 between AI girlfriends and coding assistants as a general rule.
My father uses ChatGPT extensively. My friend, whos an electrician, but has 0 things to do with computers, even called it Chat once and I said who? Because for me its ChatGPT. He also uses it extensively. Although I would bet they won't be willing to pay, advertisements will eventually hit them. And with inference prices going down, with distilled models being used, OpenAI will profit, and people will still hapily use it for whatever random queries they have. Exposure is the currency and OpenAI will have infinites of it for the foreseeable future.
Chat.com is ChatGPT so likely that's why he called it Chat.
Oh damn i missed it. Could be that, but were from a non-english country so not sure.
The juxtaposition of quotations at the head of this article will seem even more silly as AI progresses. The user-centric culture that Steve Jobs championed at Apple is quite orthogonal to the trajectory of artificial intelligence. AI has been under collective development for decades. Along this trajectory ChatGPT was the discovery of a viable "product". Remembering OpenAI's documented history, ChatGPT was not the result of building a tool towards solving a specific user need. It is no accident that Apple does not know what to do with AI yet. I am hoping that they can learn from Anthropic's tool empowerment lead and from the possibilities of OpenClaw, and instrument thoughtful AI integrations for their products. OpenAI can learn from them too, but they aren't in a particularly advantageous incumbent position like Apple and Google. But whatever Apple may do, it will only be a fraction of the AI story, regardless of its consumer success. Comparing the markets of OpenAI and Anthropic highlights this diversity.
> The models have a very large user base, but very narrow engagement and stickiness, and no network effect or any other winner-takes-all effect so far that provides a clear path to turning that user base into something broader and durable.
I think this is clearly wrong. Users provide lots of data useful for making the models better and that is already being leveraged today. It seems like network effects are likely in the future too. And they have several ways to get stickiness including memory.
On the broader point, I think it's right to say that OpenAI has challenges. It simply has no differentiation beyond branding and arguably there are quite a few obvious ways it messed up and lost momentum (the board fight, trying to go in every direction at once etc.)
Today you have a phone in your pocket and you have apps on your home screen. Facebook is on your home screen, Whatsapp or X or Bluesky or whatever have a place on your home screen. Google basically is the safari app on iPhone. I don't know how many people have ChatGPT on their home screen. And soon, there will be some AI in your home screen from Apple (served by Google or another big hitter)that will be an incredible advantage.
That means OpenAI either needs to build up history with users very quickly and use that as stickiness before Apple nukes that distribution. Or they need to find a way of being another device that every living person has in their pocket.
Every attempt at doing that so far has been a comical failure and the way OpenAI are behaving makes me think their attempt will be no different.
OpenAI has the best cross-thread memory system in ChatGPT amongst all the frontier LLMs and it's not even close.
Is this a market advantage that is a moat? I don’t see why this wouldn’t be at best a few months lead over the competition. It’s certainly not meaningful to user acquisition.
And the reason I stopped using it
Think more like what Microsoft did by being everywhere enterprises already were: integrations, admin controls, compliance posture, procurement-friendly packaging. OpenAI doesn’t need to “invent all experiences” if it can be the default inference layer that’s easiest to buy, govern, and instrument inside large orgs—especially if it can show auditors a cleaner story than “random employees piping data into a consumer chatbot.” This is the less sexy but very real wedge: the assistant becomes a governed interface to computation.
https://paulgraham.com/fundraising.html
I would love to dunk on this or something, but the lesson is that it's all about distribution.
Sama is really good at that, and also.. gotta give props for a lot of forward thinking like the orb, which now makes a lot of sense to me, as non-Apple/Google proof of personhood.
His competitors aren't too bad at it either.
In consumer search, Google paid to be the default because defaults are basically behavioral gravity. Most people don’t churn defaults. In AI, the equivalent isn’t just “the search box,” it’s the assistant that sits inside the apps where you already spend your cognitive budget—design, docs, email, IDE, CRM, ticketing, finance—so your prompts stop being little one-off spells and start being operations with permissions, audit trails, and repeatability.
OpenAI lost the race to nerds' hearts. In the latest benchmarks, OpenAI is simultaneously cheaper (like 50% less?) and scores hire in coding and tool use benchmarks (GPT-5.3-Codex trounces Opus 4.6), yet all the coders want to marry Anthropic. I don't think OpenAI understands how to sell, if they even had a product to sell.
I'm not so sure about that. There's a lot of people that were turned off by Anthropic, especially with the weekly usage limits. that in comparison to Codex is on the last side. And actually Codex is one of the few products that I think OpenAI has executed really well on. there's just no real equivalent in terms of actual usage that you can get for the same amount of money. Gemini is great, but it seems to be still in a state of flux. Way too much products stretched too thin. Anthropic is also okay, but it's very limited in the weekly usage you can get out of it.
What I also observe is Anthoropic pissed a lot of people off when they removed external tool usage from the subscription. OpenAI won some points and usage in codex. But what conclusions can you really draw from a few reddit posts...
its because benchmarks are nonsense and when you actually use OI models for programming they suck
”In browsers, the last successful product innovations were tabs and merging search with the URL bar.”
I see the point Ben is making even though there are a lot of nerdier innovations he’s skipping over — credential management, APIs (.closest!), evergreen deployments, plugin ecosystems, privacy guards, etc.
One aspect that model execution and web browsers share is resource usage. A Raspberry Pi, for example, makes for a really great little desktop right up until you need to browse a heavy website. In model space there are a lot of really exciting new labs working on using milliwatts to do inference in the field, for the next generation of signal processing. Local execution of large models gets better every day.
The future is in efficiency.
I think this article spends to little time on what it calls "user data". It is likely the best data pump in this segment, because it has the most 'regular' users, i.e. people who aren't IT specialists or whatever, but give the best profit when advertised to, surveilled and so on.
They'll have their guard down more often than the claudinistas and geminites, and be cheaper to somehow exploit.
I also think that more half-serious business ideas have been initially implemented against OpenAI services, i.e. most likely to fail due to a lack of proficiency in how to make an organisation work even if the core idea is sound and worthwhile pursuing.
If you were forced to choose just one of all the competing players, which is "the one" you will use?
For me, the choice is ChatGPT, not for its Codex or other fancy tooling - just the chat. Not that Claude Code or Cowork is less important. Not that I like Codex over Claude Code.
Right now? Claude, so long as they don't fold to the Pentagon's demands. It's important to me that the company at least have a pretense of ethics. If they fold, I may just use open models via DDG – I don't find code assistants very useful for my workflow anyway.
Same. I wish it wasn’t the case, but even making a show of caring about ethics is about as much as we can hope to get from a company these days.
Their existing users is an edge, but that's not much for the scale they're operating at. Users are lazy and even if you tell them "Gemini is 50 % better !" if ChatGPT isn't bad they won't switch.
Great article, but I think this is a stretch: "nor does OpenAI have consumer products on top of the models themselves that have product-market fit."
I would argue chatgpt is in the top 10 products of all time with regard to product market fit.
Isn't this kind of splitting hairs? Technically you're right, but he's obviously talking about a product that itself, independently from its underlying model, has a "strong, clear competitive lead" over would-be competitors.
Open AI seems to be jack of all trades.i randomly use chatgpt for random questions, never for a serious task. They should check how anthropic is laserfocussed on coding and b2b segment.
Codex 5.3 is way better than opus 4.6
My experience is completely the opposite. For generic, low-complexity CRUD tasks, Codex works fine. But when it comes to complex bug fixing, it completely fails, especially with middleware pipelines and complex authentication issues. Gemini also shines, codex is absolutely terrible for complex coding.
1 reply →
I’ve used Claude Code almost exclusively since its release. In the last week or two, I gave Codex a spin. So far, I’m impressed. It does seem to have reached parity. And, it doesn’t run out of tokens nearly as fast as the equivalent Claude plan.
1 reply →
Worth noting that it’s not a winner-takes all situation. There’s definitely space for differentiation.
Anthropic is in favor with developers and generally tech people, while OpenAi / Gemini are more commonly used by regular folks. And Grok, well, you know…
We have yet to see who’s winning in the “creative space”, probably OpenAI.
As these positionings cristallize, each company is likely going to double down on their user’s communities, like Apple did when specifically targeting creative/artsy people, instead of cranking general models that aren’t significantly better at anything.
> Worth noting that it’s not a winner-takes all situation.
I think it has to be for the financials to work out. Whoever is not the winner and takes all goes bankrupt.
I categorize it like this:
Claude: Programmers
ChatGPT: LGBTQ/Liberals, with a lot of censorship
Grok: Joe Rogan
DeepSeek: Jìan-Yáng
One trillion capex per year? Does that mean they need everyone on the planet to get $100/yr subscriptions to stay solvent? Without a monopoly? Or a product that most people use much?
So far it's been more like triple-digit billions per year, and most of that has been coming from the Big Tech companies' operating cash flows. Debt recently entered the picture, however.
Maybe most of that is floating between them and nVidia back and forth.
Of course not. It could be half the people on the planet need to pay $200/yr
1/10000th would not pay $20/year
People underestimate the lead OAI has with their post-5.2 models. The author does not strike me as someone who closely follows the progress frontier labs make in US and around the world.
It's a joint ignorance of how these frontier models get baked and what consumers want.
Many pundits think it's just a matter of scraping the internet and having a few ML scientists run ablation experiments to tune hyperparameters. That hasn't been true for over a year. The current requirements are more org-scale, more payoff from scale, more moat. The main legitimate competitive threat is adversarial distillation.
Many pundits also think that consumers don't want to pay a premium for small differences on the margin. That is very wrong-headed. I pay $200/month to a frontier lab because, even though it's only a few % higher in benchmark scores, it is 5x more useful on the margin.
It is the benchmark error rate, not the benchmark success %, that we actually trip up on.
Going from 85% to 90% is possibly 1/3 fewer errors or even higher, depending on the distribution of work you’re doing.
> The current requirements are more org-scale, more payoff from scale, more moat.
What moat? None of the AI providers have a moat at the moment, and the trend doesn't indicate that any of them will in the near future.
6 replies →
You pay to OpenAI or which one do you use? Do you switch regularly?
1 reply →
Funny. What lead? Gemini and Claude are much better.
Yeah. I also do not see the lead. Claude Opus writes better code and for conversation all models even Le Chat is just better than ChatGPT currently.
11 replies →
Agreed, compare the frontier models from Google and OAI. It’s like night and day. Anyone who says “the tech has caught up” has not spent even one day using Gemini 3.1 to try and accomplish something complicated.
I think the vast majority of coding us done through claude and gemini
> what a platform really achieves is to harness the creative energy of the entire tech industry, so that you don’t have to invent everything yourself and massively more stuff gets built at massive scale
I hear this, but every time I look the platforms have captured another use case that the startup ecosystem built (eg images, knowledge summarization, coding, music).
The sector is already littered with the corpses of the innovators that got swallowed by the platforms’ aggressiveness to do it all.
I have only dabbled with Claude and other AI tools, but from what I can tell, only ChatGPT has folders and a robust organization system. (Someone correct me if I’m wrong here.)
This matters a lot to me, as I use AI as something of an ongoing project organizer, and not purely for specific prompts.
So at least for me, it would be a huge hassle to move to another platform, on par with moving from one note-taking software to another (e.g., Evernote to IA Writer.)
Check Claude Projects.
Also Claude Code.
Both have "folders".
Ah I see. I didn’t notice these before. Thanks!
All they need to do is fund thousands of vibe coders to create apps and utilities for people using their model.
Like, why do I STILL have to do taxes and accounting with external tools? Why doesn't OpenAI have their own tax filing service for the people?
OpenAI should just drop their API service and build everything themselves. It's exactly what they did with ChatGPT. Build thousands of things, not just a few.
> Like, why do I STILL have to do taxes and accounting with external tools? Why doesn't OpenAI have their own tax filing service for the people?
Legal liability.
Is ChatGPT going to convince the IRS that it wasn't you that tried to cheat on your taxes, and that it was all a simple "hallucination"?
A very obvious and likely to happen strategy is to turn the emotional manipulation dial up. Make users more dependent on validation and attention the model provides.
They're already doing it, but wonder how far they'll take it.
> There is no equivalent of the network effects seen at everything from Windows to Google Search to iOS to Instagram, where market share was self-reinforcing and no amount of money and effort was enough for someone else to to break in or catch up.
What is the network effect of Google Search?
The main direct network effect is that Google uses heuristic data from users to improve their search rankings. (e.g. which links they click, whether someone returns quickly to Google after clicking on a link, etc)
Other factors that favor Google at scale:
- Sites often allow only the biggest search engine crawlers and block every other bot to prevent scraping. This has been going on for more than a decade and is especially true now with AI crawlers going around.
- Google search earns more per search than competitors due to their more mature ad network that they can hire lots of engineers to work on to improve ad revenues. They can also simply serve more relevant ads since their ad network is bigger.
- Google can simply share costs (e.g. index maintenance) among many more users.
Companies competing to buy ad space and SEO of every website on too of it.
This is confirmation bias. HN and other tech people are focusing on the programming aspect of AI more than anything else. The average user does not use it for that, and they don't care. ChatGPT became something like Kleenex.
Kleenex was exactly what I had in mind when reading other comments. And just like Kleenex, where people use whatever tissue they find and forget the word "tissue" even exists, ChatGPT seems to be becoming a genericized term that just means "AI chatbot."
ChatGPT is not OpenAI's product, it's the demo. The product is selling their technology to tens or hundreds of thousands of companies that embed it in e.g. customer support chat services.
Not many folks talking about this: https://www.tomshardware.com/tech-industry/artificial-intell...
The WH has said it hasn't approved any sales, but it's not clear China is buying, and it seem they are making good progress on their huawei ascend chips. If China is basiclly at parity on the full stack (silicon, framework, training, model), and it starts open weighting frontier models at $0.xx/M tokens, then yeah, moat issues all around one would imagine? Not surprised to see Anthropic complaining like this: https://www.anthropic.com/news/detecting-and-preventing-dist... - but I don't know how you go back from it at this point?
Not surprising, Nvidia's margin was just a huge incentive for companies/countries to develop their own solutions. You don't have to be 100% as good if you're 80% cheaper. It's unsurprising that this is being driven by Chinese companies/labs who often have a lot less funding than the US, and the big tech companies (Google, Microsoft, Amazon) who will benefit the most from having their own compute.
I've never believed in Nvidia's moat, and it seems OpenAI's moat (research) has gone and surprisingly is no longer a priority for them.
It seems like it’s really only China that’s pursuing the route of doing more with smaller/cheaper models, too, which also has a lot of potential to give the whole bubble a good shake.
To me it seems like the most obvious thing to do. More efficient models both make up for whatever you lost by using cheaper hardware and let you do more with the hardware you have than the competition can. By comparison the ever-growing-model strategy is a dead end.
1 reply →
Feels a bit crazy saying this but I can imagine a weird future where we have some outlawed Chinese tokens situation under some national security guise. No clue how that would work but nothing surprises me anymore.
1 reply →
Nvidia's margins are a wake-up call for anyone reliant on their tech. As companies in places like China pursue self-sufficiency, the competitive landscape is shifting quickly, opening up space for innovation from unexpected sources.
China doesn't need to buy it. They can continue their policy and look good.
They've already found a better route. Buy it elsewhere e.g. in Singapore. Train their models there using Nvidia hardware.
Ship the result and fine tune back in China.
So "China" is and has always been buying it. No difference. The politics can keep raging.
This is interesting to me. I thought that the reason for deepseek delay was because of the insistence ( by the politicians) to use huawei chip[0]. But that was last year August.
Anything changes in between?
[0]: https://www.reuters.com/world/china/deepseeks-launch-new-ai-...
GLM-5 was trained entirely^ on Huawei Ascend chips. https://z.ai/blog/glm-5 / https://tech.yahoo.com/ai/articles/chinas-ai-startup-zhipu-r...
(^edit, I don't know for certain entirely is accurate - edit again, found a chinese source saying their image model is end to end ascend, or at least, domestic: https://zhuanlan.zhihu.com/p/1994775762516080044 & https://www.guancha.cn/economy/2026_02_12_806895.shtml)
1 reply →
Same question for Atrophic.
Personally I only see Google (Gemini), X (Grok) and the Chinese models having a chances to still be alive in 1-2 years.
Anthropic are making a very convincing play for business and "enterprise" customers - first with Claude Code and now with Cowork and especially Claude for Excel. The revenue growth they've announced has been extremely impressive over the past year.
Well, the public reception seems to be changing, after tweets like this: https://x.com/AnthropicAI/status/2025997928242811253
Also, I liked Anthropic because they were focused a lot on safety, but after the Pentagon stuff, it seems like they dropped their focus on safety.
X has only brand recognition right now, and an extremely toxic one.
Big customers may buy but won't give them logos, people who are offended by Musk's worldview won't pay them either. You don't do well with a toxic brand: just look at Ye having to buy full page apologies ads to try and sell a record.
X?
Don't they have the biggest budget and largest GPU farm?
Also grok-4.1-fast was one of the top models for a long time, especially in real world usage.
It's funny you say that, I thought this would be an article about how Anthropic have managed to produce a better (coding) product than OpenAI despite having 1/10th of the funding.
The new versions of Opus (4.5 and 4.6) are absolutely amazing - first time I've felt it necessary to throw hundreds of dollars in a single month at Cursor.
I heard similar things about the older models too (Sonnet 3.5 beating GPT-4 etc.) but sadly only jumped on the Cursor train in the last 12 months or so.
The problem is not the models, is the moat and budget. Google and X still have money and are profitable, all the other AI companies are losing billions per year.
And customers will happily switch from one model to another in a heartbeat.
> Personally I only see Google (Gemini), X (Grok) and the Chinese models having a chances to still be alive in 1-2 years.
I'd make it more general - the only AI tokens providers that will last past the bubble are those companies that are already self-sustaining via other product channels.
Any company that has AI as their one and only product aren't going to survive.
Anthropic* lol, unintentional...
Google might step up soon and they already have a massive user base.
Google “How to send a get request using Java”.
>import java.net.URI; import java.net.http.HttpClient; import java.net.http.HttpRequest; import java.net.http.HttpResponse;
public class GetRequestExample { public static void main(String[] args) { // Define the URL String url = "https://api.example.com/data";
}
Vs Chat GPT
> import java.net.URI; import java.net.http.HttpClient; import java.net.http.HttpRequest; import java.net.http.HttpResponse;
public class GetRequestExample {
}
Chat GPT is a bit clearer, but both are good.
It’s really Google’s race to lose, but we are talking about Google here. They’re very hit or miss outside of Search
This is what they need to compete: https://www.cnx-software.com/2026/02/22/taalas-hc1-hardwired...
Demo: https://chatjimmy.ai/
I just cancelled my paid Plus subscription. I do not want to give away money.
Who cares? OpenAI doesn't care about how it affects entire industries
Wasn't OpenAI's moat buying up all the RAM or Nvidia cards?
They won't. They'll seek regulatory capture.
They have already succeeded. Never had a plan to compete.
Tech companies are one of the jewels in America's (USA's) crown. If we build a bunch of huge AI companies, rivals will probably continue to release open AI models which undermine the US's influence in the world.
> Every few weeks they leapfrog each other. There is variation within those capabilities, it’s possible to drop off the curve (Meta, for now) or fail to get onto it (Apple, Amazon, Microsoft, for now), or remain six months behind the frontier (China), or rely heavily on other people’s work (China, again)
I really dislike this narrative where it's always China = bad, and US companies = good.
These labs all copy from each other. OpenAI and Anthropic have "distilled" each other models too and routinely poach key researchers from competitors. Not only that, there's evidence Sonnet 4.6 has heavily distilled Deepseek R1 too, in fact, if you ask Sonnet 4.6 in Chinese who it is, it will tell you it's a Deepseek model.
Chinese are the only ones publishing papers on their models non stop.
The whole AI race is entirely based on blatant copyright infringements and copying each other.
I'm not a huge fan of OpenAI as a company, but I subscribe to ChatGPT. I regularly try put the competition, but (for me) ChatGPT deliveres better results.
Give me an open source or non-American product that delivers the same quality, and I'll switch in an instant.
FWIW, this is how capitalism is supposed to work! Competition is driving AI forward at a fantastic pace!
Sometimes I like to imagine what this would be like if the technology had appeared 25 years ago.
First off, nonetheless open publishing stuff. Everything would have been trade secrets.
Next off no interoperable json apis instead binary APIs that are hard to integrate with and therefore sticky. Once you spent 3 or 4 months getting your MCP server setup, no way would you ever try to change to a different vendor!
The number of investors was much smaller so odds are you wouldn't have seen these crazy high salaries and you wouldn't have people running off to different companies left and right. (I know, .com boom, but the .com boom never saw 500k cash salaries...)
Imagine if Google hadn't published any papers about transformers or the attention paper had been an internal memo or heck just word2vec was only an internal library.
It has all been a net good for technological progress but not that good for the companies involved.
Could they have even trained the models 25 years ago? Wikipedia was nothing close to what it is today and I know folks here like to mourn the fall of the open web, but it's still orders of magnitude larger today than it was in 2001. YouTube, so many information stores that simply didn't exist then.
Maybe not 25,but IBM Watson beat humans at Jeopardy over 10 years ago. The technology has been there, the difference is the willingness to burn money on it in hopes of capturing exponential revenue from disrupting industries.
Obviously the costs have come down but if IBM felt like burning 100 Billion in 2012 I'm pretty sure they could have a similarly impressive chat bot. Just not sure how they would have ever recouped the revenue.
1 reply →
The book archives are a big one as well, all the journals that have been published digitally throughout the 2000s, and all the newspapers.
Though with some types of models (specifically voice) it has been discovered that a smaller high quality dataset is better than a giant dataset filled with errors.
It would be an unpopular opinion but I am here to say it:
OpenAI has the best model, that is how they are going to compete.
Their chatbot business could be in trouble, but Gemini needs a LOT of work to make it better to use too.
Coding wise, it has become very competitive. They need to sell better and sell aggressively
sammy boy needs to pull a rockefeller and buy up all the competitors. Maybe that's what all these backroom deals about datacentre investment will amount to...
This was poorly worded but indeed rockefeller was the richest man ever by selling a commodity. But he did it by merging with all his competitors. Not sure Altman could pull that off here because most of the other models are attached to massive tech co's that can use AI as a loss leader for other profitable services.
This article is significantly better written than most anti-OpenAI/AI articles, and for that I am really grateful. I am generally an AI booster (lol), so I am happy to read well-considered thought pieces from people who disagree with me.
That being said...
> The one place where OpenAI does have a clear lead today is in the user base: it has 8-900m users. The trouble is, there’re only ‘weekly active’ users: the vast majority even of people who already know what this is and know how to use it have not made it a daily habit. Only 5% of ChatGPT users are paying, and even US teens are much more likely to use this a few times a week or less than they are to use it multiple time a day.
This really props up the whole argument, because the author goes on to say that OpenAI's users are not really engaged. But is "only" 5% of users paying of a 8-900M user base really so inconsequential? What percentage of Meta's users are paying? Google's? I would be curious to see the author dig deeper here, because I am skeptical that this is really as bad as the author suggests.
Moving on to another section:
> If the next step is those new experiences, who does that, and why would it be OpenAI? The entire tech industry is trying to invent the second step of generative AI experiences - how can you plan for it to be you? How do you compete with this chart - with every entrepreneur in Silicon Valley?
Er, are any of these startups training foundation models? No? Then maybe that is how you compete? I suppose the author would say that the foundation model isn't doing much for OpenAI's engagement metrics (and therefore revenue), but I am not sure I agree there.
Still, really good article. I think it really crystalizes the anti-OpenAI argument and it gives me a lot of interesting things to think about.
> But is "only" 5% of users paying of a 8-900M user base really so inconsequential? What percentage of Meta's users are paying? Google's? I would be curious to see the author dig deeper here, because I am skeptical that this is really as bad as the author suggests.
The difference is in the unit economics. OpenAI has to spend massively per free user it serves. The others you mentioned have SaaS economics where the marginal cost of onboarding and serving each non-paying user is essentially zero while also gaining money from these free users via advertising. Hence, the free users are actually a net positive rather than an endless money sink.
Keep also in mind that AI has always been, and will always be, a commodity. The moment you start forcing people to convert into paying customers is the moment they jump ship at scale.
Just something to keep in mind.
> What percentage of Meta's users are paying? Google's?
The advertiser based business model for those companies makes your question/thought process here problematic for me. Historically speaking Google and "Meta" (Facebook) were primarily advertising provider companies. They provided billboards (space and time on the web page in front of an end-user) to people who were willing to buy tht space and time on the billboard. The "free access" end-users would always end up seeing said billboards, which is how they ended up "paying" for the service.
So most of Meta/Google end-users were "paying" users. They were being subsidised by the advertising customers paying for the end-users (who were forced to view adverts). The end-users paid with interruption to the service by an advert. [0]
In that context it feels a little like you're comparing apples to dave's left foot, as OpenAI hasn't had that with advertising ............ historically [1].
--
[0]: yes ad-blockers, yes more diverse revenue income streams over the years like with phones, yes this is simplified yadayada
[1]: excluding government etc. ~bailouts~ investments as not the same as advertising subsidies, but you could argue it's doing the same thing
Yes -- but both Google and Meta didn't start off as an advertising company - they started off providing a service a lot of people liked, and then eventually added ads to it. My assumption (somewhat implicit, admittedly) is that there's no reason OpenAI couldn't do the same. I can understand why that might be controversial, though.
But honestly, if OpenAI can't figure out ads given all their data and ability, they deserve to fail. :P
2 replies →
You’ve missed the point completely - if the important experiences are things built on top of foundation models, where the model itself is just an API call, then you don’t need to have a foundation model for build them and the model is just commodity infra
Yes, but OpenAI has 900M+ user reach, plus staggering amounts of cash, plus early access + deep integration with the latest and greatest models. I hardly think that is tantamount to "just an API call".
1 reply →
To say "except for distribution" OpenAI has few advantages is like saying "except for location" this retail store really doesn't stand a chance.
I stopped reading once Evans emphasized consumer product. That was never a good strategy to sell SaaS, and I don't see how that changes.
OpenAI is the Yahoo of AI.
For me Codex beats Claude.
Same here. I moved from claude code to codex. But switching costs are so low that I will just bounce between them depending on which one is better at the time. I think for developers at least, openai don't have stickiness.
I use Codex for stuff that touches the UI. Codex is better and faster at the backend stuff. And I usually instruct it on where to copy UI elements from.
A basic Claude Code plus a basic Codex subscription is just 40 euros and it beats a single 200 euro Pro subscription. For me at least.
maybe openai is another docker.. and we are waiting for the 'k8s'
[dead]
The main problem with OpenAI/Anthropic is that their only moat is their models, and it has been proven that you can clone a model through distillation. Although the performance is not exactly the same, it gets very close to the original.
[dead]
[dead]
[dead]
[dead]
[dead]
> The one place where OpenAI does have a clear lead today is in the user base: it has 8-900m users.
There is no way that number is an accurate reflection of the number of actual human users of their service. I could believe they have 8-900m bot/fraud accounts in their databases, maybe, but not real users.
I suspect I am one of those 1bn users by their metric. I have an account, and I sometimes query it. I also query Claude and Gemini. I have zero loyalty, if I run out of tokens on one, I will just pick up the conversation on another provider. Perhaps I am using them wrong, but the amount of babysitting I have to do anyway, I don't find it that tedious to stay on the same topic during a swap.
There's no way I would spend $200 a month on any of them, not even $20 considering how few 'tokens' you get. I can see how these tools would be useful to my workflow, but I cannot use them as they are priced 100x too high for me to be reliable.
I have a feeling that would be true for the vast majority of these AI tool users. I really am not sure how these companies are supposed to become profitable. But SV is a bit insane that way.
i used to use them that way until I got a IDE with AI and is way better for my development than copying and pasting into the chat. It can have the whole project as context,plan features with me, etc. I use it a lot in a way that I cant see why I would go to programming without it right now. It takes time to adjust to it to learn how it works and all but it's worth it