Platforms usually deliver significant value that is hard to replicate. OpenAI doesn't have any such thing. It's trivially replaced, and there's many competitors already. OpenAI is ahead of the curve, but they don't seem to have any particular way to do sticky capture. Migrating to a different LLM is an afternoon's work at most, not nearly the complexity of porting an app between OS' or creating a robust hardware driver model.
Yeah, I'm extremely loyal to ChatGPT Plus and Codex, but is't because OpenAI has a native Mac app that I like, and Codex included with Plus and has served me well enough to not look at Claude. I like GPT-5 quite a bit as a user. I'll concede none of these are small things - they've had my money for 2+ years - but they're not gigantic advantages either.
At an enterprise level however, in the current workload I am dealing with, I can't get GPT-5 with high thinking to yield acceptable results; Gemini 2.5 Pro is crushing it in my tests.
Things are changing fast, and OpenAI seems to be the most dynamic player in terms of productization, but I'm still failing to see the moat.
Their platform mostly just works. Their api playground and docs are like 100x better than whatever garbage Anthropic has.
I think their UX is way better, and I can have long AF conversations without lagging. I can even change models in the same conversation. Basic shit Anthropic can’t figure out (they can fleece their 20x max subscribers tho)
I think if they get the AI human interface right, they will have their iPhone moment and 10x.
The platform is just a search tool and extended processing modes. That is easily replicated elsewhere.
The only moat they have is the fact that you still need a GPU of some kind to reliably run even a tiny LLM. But the gap between what absolutely needs a server farm and what can be ran on a store bought gaming computer is quickly closing. You can already run mixture of experts models on gaming rigs with a high degree of usability compared to just one year ago. And that tech continues to be pushed further and further. It's only a matter of time until we see ChatGPT levels of access running on a quad core laptop totally offline. And once that happens, all such a system would need is the correct tooling on top of the AI model "brain" to make it usable.
And beyond that, what if you could have an AI model on an ASIC-style add-in card? Where's their moat then?
Don't forget about Macs. Top models can run even fairly large LLMs (although time to first token is... not great). But even midline can certainly run LLMs in the ballpark of ~30B params very well, which is where things start to get interesting IMO.
I'd say their DX is way better compared to the competition. The playground, tooling, and web experience with documentation is far superior to the competition (even tho it has issues sometimes). User experience is key in a sea of the same shit.
I mean you could say the same about a Macbook or iPhone/iPad, but for the actual people (not HN users lol) out there, they vastly prefer Apple to HP, Dell, etc. Due to their wallet some can't though.
There are literally thousands of other laptops that do the "same thing" (computer for doing shit).
Those who say otherwise are usually broke and know deep down that given proper purchasing power, they too would prefer to use a $3k Macbook Pro than some POS Dell.
Same with android.
Everyone knows it is cope based on PP, it is just in poor taste to actually call it like it is (idc)
Apple had innovative products that they went very heavy in brand based fashion merchandising. In addition they were a legacy brand with a generally favorable reputation and solid recognition. They built a strong moat based on those characteristics and finally hit the mass market non-tech target demographic with the most widely used emerging technology since the personal vehicle. Apple did this while successfully merging a hardware, software, and marketplace platform. OpenAI has some interesting software but has an incredibly long way to run and extremely unlikely path to becoming anything like Apple. Not only that, they are in a market that a lot of the general population finds questionably valuable if not outright unappealing.
OpenAI is dynamic for consumer apps. Anthropic seems much better at productizing AI that you can actually build with, while also catering to enterprise in their own productized offerings
Also Claude Opus 4.1 runs multidimensional circles around GPT-5 in my view. The only better use case for GPT-5 is when you need it to scrape the web for data
Too bad Anthropic fucks over their 20x max subscribers. Their whole opus usage limit bullshit in favor of sonnet 4.5 which is objectively worse regardless of whatever they say. They clearly want to save money and take our $200.
Interesting, so it's not just me who's finding Gemini 2.5 Pro to be the quiet leader? Deep Research also seems to be better in it, and the limits for that are far more generous to boot (20 per day on Gemini!).
Makes one wonder if Google will eventually sweep this field.
I don’t think they will get any moat. I might be wrong on this of course, but I don’t see a killer feature for these stochastic parrots that can’t be easily replicated
Never mind the phrase. If your parrot can compete in international math and programming competitions at the gold-medal level and make entire subreddits fail the Turing test, I would like to borrow your parrot.
"the term stochastic parrot is a metaphor, introduced by Emily M. Bender and colleagues in a 2021 paper, that frames large language models as systems that statistically mimic text without real understanding"
Much of the value I get from ChatGPT is based on it's memory system that has a good profile on me. For example if I ask it to find me something to eat at X restaurant, it will already know my allergies, dietary preferences, weight goals, medications, other foods I like, etc and suggest an item based on that, all workout me explicitly telling it.
Moving from ChatGPT to Claude I would lose a lot of this valuable history.
Or you could type up "My allergies are X, Y, Z, I have the following preferences..." etc. and put it into whatever chat bot you like. Obviously this is a bit of a pain, but it probably constrains significantly how much of a premium ChatGPT can charge. You might not bother if ChatGPT is time and a half more expensive, but what if it's 3x as much as the competition? What if there's a free alternative that's just as good?
I pay for the $200/mo ChatGPT, to me that's insanely cheap compared to the value it provides. Better pricing is highly unlikely to make me switch. If a competitor were able to sustain a lead in model intelligence/capability then I'd consider it.
Even simpler, ask ChatGPT "How would you describe my dietary preferences and restrictions?", maybe throw in some personality guidance of "You are training my executive assistant".
Have you tried asking ChatGPT to output everything it knows about you to a format easily digestible by LLMs? Does the memory stick between model switches?
I like to ask each llm what it knows about me. I feel like I could take that output and feed it into another llm and the new one would be up to speed quickly....
You could literally ask it to write out everything it knows about you into a form usable in a CLAUDE.md file, put that in the directory you're using e.g. claude code in, and boom.
The play OpenAI is making has nothing to do with the underlying models any more. They release good ones but it doesn't really matter, they're going for being the place people land when they open a web browser. That is incredibly sticky and not easily replaced. Being the company that replaces the phrase "oh just Google it" is worth half the money in the world, and I think they're well on their way to getting there.
I agree, in general. I don't know what the world looks like in 10 years if all of the weird attempts at fitting an LLM as a replacement to what we have currently actually works, however. Facebook is probably the closest analogy, where there's plenty of room to grow, but at some point you're going to have the OS builders shut down your efforts unless you want to build your own OS.
I do say ChatGPT when referring to LLMs/genAI in general, but I do hate saying it as it is nowhere near as nice to say as "google". I will switch immediately once something better comes up.
“Chat” is already in the youth lexicon, originally referring to an amorphous blob of live stream viewers. It now kind of refers to a non-existent but omnipresent viewer of your life.
I think ChatGPT might turn into just “chat” as the next evolution of the term.
I actually prefer Google Gemini. 2.5 is free and works awesome for what I need AI for. It just made my resume I uploaded immeasurably better last night.
> Migrating to a different LLM is an afternoon's work at most, not nearly the complexity of porting an app between OS' or creating a robust hardware driver model.
I question this. Each vendor's offering has its own peculiar prompt quirks, does it not? Theoretically, switching RDBMS vendors (say Ora to Ingress) was also "an afernoon's work" but it never happened. The minutia is sticky with these sort of almost-but-not 'universal' interfaces.
> I question this. Each vendor's offering has its own peculiar prompt quirks, does it not? Theoretically, switching RDBMS vendors (say oracle to postgres) was also "an afernoon's work" but it never happened. The minutia is sticky with these sort of almost-but-not 'universal' interfaces.
The bigger problem is that there was never a way to move data between oracle->postgres in pure data form (i.e. point pgsql at your oracle folder and it "just works"). Migration is always a pain, and thus there is a substantial degree of stickiness, due to the cost of moving databases both in terms of risk and effort.
In contrast, vendors [1] are literally offering third party LLMS (such as claude) in addition to their own and offering one-click switching. This means users can try and if they desire switch with little friction.
Moreover, it's trivial to run several LLMs side-by-side for a while and measure the success of each, then migrate to the one that performs the best. And you can even migrate in-progress chats since all the context is passed on each call anyway.
The current LLMs support data export/import inherently because the interface is pure text.
All one needs to do is say something like “tell me all of personalization factors you have on me” and then just copy and paste that into the next LLM with “here’s stuff you should know about how to personalize output for me”
> The minutia is sticky with these sort of almost-but-not 'universal' interfaces.
True, but that's not really applicable here since LLMs themselves are not stable, and are certainly not stable within a vendors own product line. Like imagine if every time Oracle shipped a new version it was significantly behaviorally inconsistent with the previous one. Upgrading within a vendor and switching vendors ends up being the same task. So you quickly solidify on either
1) never upgrading, although with these being cloud services that's not necessarily feasible, and since LLMs are far from a local maxima in quality that'd quickly leave your stack obsolete
or
2) being forced to be robust, which makes it easy to migrate to other vendors
It's reasonable to question it, but there's a fun Chinese paper (https://arxiv.org/abs/2507.15855) where they attempt to create a system of prompts that can be used with commercial LLMs to solve hard maths problems.
It turns out that they can use the same prompt system for all of them, with no changes and still solve 5/6 IMO problems. I think this is possibly iffy, since people might have updated the models etc., but it's pretty obvious that this kind of thing is how OpenAI are doing their multi-stage thinking thing for maths internally.
Consequently if prompt systems are this transferable for these hard problems, why wouldn't both they and individual prompts, be highly transferable in general?
No, changing rdbms is a totally different challenge. They provide predictible reproducible output which are very sensitive and brittle to the slightest minor change in the input, while with LLM you expect the exact opposite.
Changing the LLM backend in some IDE is as complicated as selecting an option in a dropbox for those who integrate such a feature. They are other scenarios where it might be a bit more complicated to transition of course, but that's it.
If you are doing things “properly” then you have good evals that let you test the behaviour of different LLMs and see if they work for your problem.
The vendors have all standardised on OpenAIs API surface - you can use OpenAIs SDK with a number of providers - so switching is very easy. There are also quite a few services that offer this as a service.
The real test is does a different LLM work - hence the need to evals to check.
If you took any of current top 3 models from me, I would not miss the deleted one in the least. I run almost every non-trivial prompt through multiple models anyway.
Google search requires a lot of resources to crawl, keep indices up to date, and provide user level significance (i.e. different results to different users). Then couple it with their other services (Google Maps, etc).
The competitors have not come even close to Google's level of quality.
With LLMs, it's different. Gemini/Claude are as good, for the most part. And users don't care that much either - most use the standard free ChatGPT, which likely is worse than many competitors' paid models.
It's not just the quality. The are people who do complain about how they perceive it significantly decreased over time. Yet there are many other factors, including presence as default search engine in so many setup out there.
Google was always terrified by the fact that they had no moat in Search. This was clear from interviews and articles at the time. That's why they decided to roll up the ad market instead, and once they had the advertisers Search became a self-fulfilling monopoly.
Google Search would be moatless if not for the AdMob purchase.
they understand that, and that's why they're making it sticky by adding in app purchasing, advertising, integrations. also why they hired OGs from IG/FB. They are building the moat and hoping that first to market is going to work out.
they are trying to become/replace google. they are first to market for an entirely new query paradigm and in app purchases and advertising are just one aspect of a platform.
And business partnerships, government partnerships, and AI regulation (to establish laws that keep competitors out). Sam knows they have no moat and will try every avenue to establish one.
That's why OpenAI is hard pivoting towards products now. The big one IMO is Instant Checkout and Agentic Commerce Protocol. ChatGPT is going to turn into a product recommendation engine and OpenAI is going to get a slice of every purchase, which is going to disrupt the current impression/click adtech model and potentially Google and Amazon themselves. It's an open question how hard they can do this without enshittifying ChatGPT itself, but we'll see.
The notion that people would be willing to let LLMs spend money is, frankly, insane given the hallucination problems that still don't have any clear solution in sight.
OpenAI's moat is the data you give it. It's the same reason so many people have GMail accounts, even though we all know Google sucks. It's not that you like GMail better than any other email service, it's because migrating to another service is a pain in the ass.
OpenAI will either use customer data to enshittify to a level never seen before, or they will go insolvent.
OpenAI turned that research into a product before Google, which is a huge failure on Google's part, but that's orthogonal to the invention of what powers modern models.
You mean the social network that is currently dying the same death as countless other platforms before it, just on a larger scale?
Maybe some are too young to remember the great migrations from/to MySpace, MSN, ICQ, AIM, Skype, local alternatives like StudiVZ, ..., where people used to keep in contact with friends. Facebook was just the latest and largest platform where people kept in touch and expressed themselves in some way. People adding each other on Facebook before others to keep in touch hasn't been a thing for 5 years. It's Instagram, Discord, and WhatsApp nowadays depending on your social circle (two of which Meta wisely bought because they saw the writing on the wall).
If I open Facebook nowadays, then out of ~130 people I used to keep in touch with through that platform, pretty much nobody is still doing anything on there. The only sign of life will be some people showing as online because they've the facebook app installed to use direct messaging.
No, people easily migrate between these platforms. All it takes is put your new handles (discord ID/phone number/etc) as a sticky so people know where to find you. And especially children will always use whichever platform their parents don't.
Small caveat: This is a German perspective. I don't doubt there's some countries where Facebook is still doing well.
>No, people easily migrate between these platforms.
No? It's rare for these platforms to survive, the one that was closest to challenging Facebook was kneecapped by the US government.
The time between the founding of MySpace to Facebook was a little over a year. Instagram has been the largest social network for close to decade now, and it's not like others haven't been trying. META is up 600% over last 3 years. I'm really question your definition of the word "dying"
FB in particular is becoming deader and deader every month, and it's only a matter of time before something else comes along that sucks their attention away.
People say you're wrong but I agree. Facebook is nothing more than a rent-seeking middle man between you and your friends/family. Instead of just talking to your family normally, like over the phone, now you have to talk to them in between mountains of Sponsored Content and AI-generated propaganda. It provides no productive value to the world except for making the world more annoying and making people more isolated from one another.
When you realize this, you realize that a lot of other supposedly valuable tech companies operate in the exact same way. Worrying that our parents' retirement depends heavily on their valuations!
I mean, technically no, FB has a network effect of the other people on it either being the people you want to talk to, or the people you want to advertise to.
That's a precise, incisive observation: OpenAI is trivial (any AI provider is), supported by evidence as demonstrated. It has no claim to operating software that's specifically distinct from others.
