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There is a lot of value from LLMs but it is something that I can switch easily. Yes, some frontier models are much better but users can still chose to use cheaper models for most of the work. In fact most applications, through which people will interact with LLMs anyway, will not need frontier models unless they offer "chat with AI". Anything that solves specific problems (even multiple problems) does not need frontier LLMs.

Anthropic and OpenAI will have to become more of the end user application stack. Files, calendars, emails, photos, and much more have to pass through them for them to keep making money. Else they cannot make money like the way they have been in this early era of LLMs.

Switching models is easy as a solo developer. Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc. I think Anthropic will look a lot more like a cloud provider like AWS or GCP. Same-looking product, very high switching cost that would have to be driven at the CIO-level because of all the integrations that have to be redone, IP concerns etc. And ultimately they are selling compute capacity.

Edit: I should clarify that I don’t think this justifies their valuation. It puts them in competition with much more entrenched players with established customer bases, and who aren’t in massive debt to provide their compute. I’d also like to distinguish between a model provider as someone who provides weights vs a model provider who connects their GPUs and models to your codebase and internal systems - I think the latter is where the sustainable business is.

Incidentally this is why I still feel Google is well-positioned in the long-term AI race. If they can remove their head from their ahh and make a coherent product offering across Workspace, GCP and Gemini, they could become as entrenched as MS.

I would assume AWS is probably the most interested in acquiring Anthropic out of the three major cloud providers.

> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc

I don't think this is entirely true. Companies are deploying open-source LLM gateways to be able to do that very easily now. Today, you can switch Claude CLI to any model besides Anthropic via https://github.com/BerriAI/litellm and there are major companies doing that.

This works with your favourite ADEs such as Orca as well so I disagree with this premise. The whole experience of switching is pretty seemless based on personal experience.

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We have like a dozen different LLM tools available to us and it's as easy as clicking on a dropdown to switch in every single one of them, and we have several thousand employees. Self-hosting with the cheaper OSS models is also becoming more and more attractive for larger orgs.
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Working for a 10k+ corporate and we made it pretty easy to switch to any provider, people here can use Anthropic's, OpenAI's, and our own self-hosted open weight models very easily. It's one drop-down or `/` command away to switch between them.

I think other companies are probably doing the same, the moat of a AWS/GCP/Azure is much deeper with how contrived it is to migrate between them even if you abstract as much as possible with something like Kubernetes.

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> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc

Once the cost reaches a threshold, everything is doable. We ditched Datadog in less than a month. Someone I know had their company ditch slack in a quarter and google cloud usage of 100+ million in two. Everything is doable.

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> Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc.

I'm not so sure about this. I guess it depends on how well people did their job there.

Ideally, whatever people built is loosely coupled to that third-party resource, meaning that switching cost will stay low.

After all, it's probably just prompts + an API layer. Unless one micro-optimizes their prompts for claude (which then breaks once a new checkpoint drops, hence is a bad idea regardless), pointing them towards a different API endpoint should be doable.

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Switching LLM providers as a company is not, once all your employees have it integrated with GitHub, their IDE, etc.

Speaking as someone who has been at professionally this since the 1980s, I suggest that while sometimes switching costs and network effects happen "organically," in this century businesses devote enormous amounts of attention to artificially building switching costs.

It's such a dirty practice that we have a four-letter word for it, a "moat." But of course, the moat isn't really to keep competitors out of a market, it's actually to keep customers trapped within it.

I fully expect every one of these AI providers to put as much work into trying to trap their customers within their ecosystem that they do to improve their capabilities.

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I think you'd be surprised. I've seen orgs entirely switch fundamental tech choices to save 10%.

Once they realise that you can use Deepseek / GLM for 10% of the cost these labs are done.

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My company switched from direct access with providers to AWS Bedrock. Now we just pick which model we want from the list exposed by Bedrock. We can also leverage tools like T3 which allow hand off from one model to another.
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Model switching behavior is going to be far more complicated.

First, everyone and their mom is selling AI now. It is being bundled in nearly every product. Buy CRM to run your company - they will upsell you their bespoke AI - mostly RAG/chatbot using the data inside the platform. This is an important area because today lot of companies are trying to build their own AI bespoke workflows. But companies like SAP, Oracle will spend money on improving this aspect. And people who buy/use AI for this purpose don't care if the underlying AI is Claude or not.

Then there are cloud providers. You can get Claude, OpenAI from AWS Bedrock etc. They will take the heavy lifting of changing integrations, IP concerns etc to keep people on their platform. With time expect them to make it even easier, not harder to switch models. Also, they will push for open source models because it will be more profitable.

Lastly buying from direct providers. This is here the lock in comes in. But I believe fewer and fewer enterprise will buy directly - many preferring to buy against their cloud commitments.

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It's trivial to switch. The company I work for has 1k employees has already switched like 3 times in the last two years.
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| Switching LLM providers as a company is not

I really think you overestimate the level of lock in here. If a companies tells the devs to use X because it cost 1/10 of the price they will just have to suck it up and switch.

I didn't particular want to work on a "all in agentic project" but that the nature of being employed.

The same LLM we use day to day will make it trivial to switch out providers in our infrastructure.

My F500 company switched ~10k employees of Claude to copilot in 30 days. Google did similar between Jetstream and Claude. The moat just isn’t there right now
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With some gateway inbetween managing the model responses, MCP and skills (see https://modelcontextprotocol.io/seps/2640-skills-extension) this becomes very easy
I think the future will be a lot different they we expect, AI is going to be the infrastructure layer while there will be toolings for each processes, so switching between model is a built-in feature, i.e. the tools will inject specific prompt or context based on the models, and all these are designed by people selling the tools, hence, a moat?
Let's say that the face for largest foundation model slows down enough to make the companies cloud-like, instead of whatever they are mow. Imagine the free credits that OpenAI would consider giving you as long as they are spent on migration out of Anthropic. They could even classify conversations by themselves.
VS code or other ides with multiple providers makes it pretty easy.

Also for larger companies like Amazon the danger is they replace Anthropic completely with self-hosted models.

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This is why you recommend tools like OpenCode or OpenClaw that commoditize that layer.

I am really surprised that companies who are worried about AI spend don't try that route.

Depending on how the company leverages them, it's super easy.

For us it's as easy as clicking a dropdown. The copilot vs code extension allows for this ez pz, the same is true for companies that implement an AI gateway for other tooling.

Integrations with Github and IDE are nothing. It's like changing your email software.
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Totally agree with your Google thesis. I would never count them out. I say that as someone that uses Claude (and a little chatgpt), but not Google's AI at the moment.
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Switching LLM providers as a company is even easier than a solo developer, most large companies I know are using AWS Bedrock and selecting another model is basically just a checkbox for them
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nah it's pretty easy.

it's easier than changing okta

it's easier than changing google docs and even Gmail

it's easier than migrating cloud

etc.

and we're talking several magnitudes easier too!

What?

Have you used Copilot at a company?

I can literally change my model in 3 seconds.

The moat is as shallow as it gets. Investing in a single LLM provider at the moment would be a mistake.

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Actually LLMs themselves make changing LLM provider or harness a non-issue, in my experience.
A gateway like GoModel can make switching transparent, along with the many other benefits you get with a gateway.
It’s literally a menu in Copilot.

The model is just some REST endpoint you switch out even in a lot of enterprise setups.

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If only there was a tool that could automate the switch/transition from one LLM to another...
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People seem very unimaginative about the ways in which somebody equipped with a lot of intelligence and compute, and control over both, might make money.

The recent Anthropic push into biomedical research gives a clue.

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a big move into end-user software would mean that they have to compete heavily with their own largest customers. The economics of offering SaaS are also under meaningful pressure and don't warrant anywhere near the valuation that is being suggested
The biggest moat with applications like MS Office is compatibility. Sharing a slide deck or spreadsheet with others is a simple decision, you know they have it or have software that can read/write it.

I don't get the need to have Anthropic build their custom versions of MS Office apps, I can tell Claude to generate a word doc from a wiki page and it does a pretty damn good job. Anthropic's statistical median level of software that they had Claude create isn't going to replace Office apps to the point where companies cancel/stop renewing their MS Office subscriptions/licenses.

The other element is trust. Do end users trust their data in Anthropic's systems? A lot of people get creeped out when they search for content from one device in their household and then nearly instantaneously they start seeing ads from other devices on the same topic. How creepy will AI get if it starts consuming all your docs, spreadsheets, personal finance info, emails, etc.?

I beg to differ I already am stopping using MS office recently but that's mainly because I really dislike how they lock up the apps if your late on your annual payment. It's a grating value capture model. I'm sure I will have to get back to it at some point but in the meantime google is providing great optionality and I don't have a concern that the software stack has glaring security concerns.

On the trust thing - I don't trust anthropic and I don't think MS has been a great steward over the years either.

The moat of backwards compatibility and plugins is why MS Office has survived decades of competitors without any appreciable loss of market share.

It's hard to see Anthropic replacing it, and even if so - why bother, the revenue is miniscule. They need 100 MS Offices for the compute contracts to pencil out.

End-user software is going to be under a lot of pressure. If you're Microsoft, Apple, or Google: you can easily copy products or integrate ideas into their platform. I see companies like Adobe, Salesforce, and Oracle having to downsize significantly to stay profitable. Having said that, my in-laws still pay for an AOL email so I don't think their cashflow is going to zero soon.
Adobe seems to be in a tough spot, because so much of the lock-in is client side, I think Salesforce is fairly well protected, it's just so impossibly difficult to remove once a company has fully adopted it. Similar to the staying power of the ERPs of Oracle and SAP.
It's the same really. There have always been alternatives that can work with Adobe's various file formats. Even more aren't going to change much, at least for their enterprise key customers. This is not only the case for Adobe, but many others as well, e.g. MS office is still a thing these days, and so are things like 3Ds Max or Maya, albeit having many compatible cheaper or even free alternatives. It's not so much about features, pricing or even stability. It's about customer support. Do I want to ask an LLM and test my luck or write a GitHub issue and cross my fingers that someone will read it within the next weeks? No, I will pick up my phone or write a mail and get a response within hours if not minutes.
I ask my llm to write custom software and love the freedom to customize it to my needs. Today I do a presentation on Ubuntu with a new "Presenter" app that works offline, runs 100% in CUDA on GPU and streams videos, starts in 2 seconds, lets me demo live robotics policies in 3D simulations and Opus 5.5 wrote it yesterday. This may sound very unusual, but I think it will be common in the future: moats disappear one by one.
With no feedback loop and reasonable token use?
I would say that Apple's Create Studio can move toward feature parity faster with Adobe. My point if you're not a platform provider it's going to be harder to make a profit.
The risk for Adobe isn’t that we replace their software with some AI generated alternative. It’s that we bypass that class of software altogether and have an AI do the work.
"There have always been alternatives that can work with Adobe's various file formats. "

And yet me and quite some others still yearn for a flash alternative. There never was one.

Interesting point that challenges the limits of LLMs!

Any of us could vibe code flash now. How to coordinate it as a dev ecosystem of designers and users?

Does it make sense for everyone to JITVibe presentation apps like the person above? Maybe we'll evolve to branding.

"Any of us could vibe code flash now. "

Surely not just prompting like this and it will one shot it. The usefulness of the flash authoring tool, was it was battle tested and polished.

But I did gave it a shot to took up developement again of abandoned www.wickeditor.com (a web reimplementation of flash). Good results, but limited time and energy for that right now.

The big problem is Photoshop. I have no love for Adobe, I proudly moved my department off of all Adobe products a few years ago. I am a big fan of open source solutions and I am always impressed at what the GIMP team (and some others) have accomplished.

But…

Photoshop is king. Everything else is behind by a solid decade. If you’re a professional the $40 a month or whatever it is now means nothing to you as well. It has the professionals are all on it, and because the price isn’t astronomical, that’s what everyone else uses who needs to use that kind of program more than once in a blue moon.

Premier? Replaceable. Lightroom? Pretty replaceable though still somewhat ahead. Photoshop? There’s only one Photoshop. And as much as I’m loathe to give Adobe any credit, it’s the best by a mile. There are too many essential features in QoL things that other programs are missing.

Luckily my department doesn’t need it, but if we did, we would simply have to accept Photoshop.

I'm not sufficiently skilled with Photoshop to gauge how well this replaces it, but you may be interested in this supposed clean-room reimplementation of Photoshop: https://github.com/storytold/photocraft
Heard about this! Haven’t had a chance to check it out yet. I’m sure once I have an actual project that needs me to roll up my sleeves with Photoshop I’ll give it a shot. I probably should have mentioned it in my original comment as a possible option
Not a graphic designer, so, truly asking out of curiosity: what are the QoL things and essential features in Photoshop? I've been slumming it with GIMP for years now and not felt anything very obviously missing, but again I'm not a pro.
Compatibility issues, which can be a huge deal partially due to near-vendor lock in. If you historically been on Photoshop, bringing your working/former projects into another software is not easy, which matters because revisiting work is common.

Not all tools are non-destructive in GIMP. Things like raw support, smart objects, retouching, etc. all either are super thin compared to Photoshop or require workarounds/a lot of manual effort. There are just lots of tools you expect in Photoshop that either don’t exist or exist in an inferior form. I can’t elaborate too much because I don’t really touch Photoshop much these days, but I work with people who do and worked in production long enough to know the expectations. GIMP is great but Adobe is a massive company with deep pockets, it’s hard to keep up. Their user experience is miserable but the tool itself is just far more robust, and a client simply isn’t going to accept that you won’t do something that Photoshop could do quickly because your alternate program can’t do it or does it with a lot more effort. That’s the reason I ultimately dropped Final Cut!

AI is pretty amazing for migrating. source: I'm using Claude to replace a large Tableau ecosystem. What would have taken years is now taking months.
I'm not sure corporate procurement has ever selected the cheapest and best option, so I think they may be fine. Plenty of reasons to avoid completely locking into your cloud provider as well.
> If you're Microsoft, Apple, or Google: you can easily copy products or integrate ideas into their platform

This argument doesn't hold water. Google tried like no one else to have a chat app and it failed miserably more than a handful of times. Same for social networks.

Sorry, I was referring to "end-user software" which in my mind is something that people pay for directly.
Adobe creative suite is $70/m. From most businesses perspective it's not something worth looking for cheaper alternatives and the alternatives has existed for a long time now.
now imagine that said customer/competitors have been uploading/generating their source code, problem reports, marketing collateral, and other IP _to the LLM company_ for the last few years.
This is the same argument we have heard many times with SaaS that would presumably get replaced by open source equivalents. In practice it does not happen because there is a lot of value in having someone else deal with a problem.
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Why haven't people switched then? Same could be said about Google search, Facebook, X etc. Claude is the de-facto SWE model now, yes you could use an open model but you would always be wondering if Claude would do better, like using Duck Duck or some other Search engine
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Yes, they know that. That’s why Claude is becoming a platform like Google Workspace.

They need to leverage Claude Code in the software industry to position themselves as the go-to platform for businesses.

Meanwhile, Google and Microsoft, which already dominate that area, seem to be dormant.

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One thing I have noticed; as a project matures frontier AI is less useful essential.

Qwen3.8 and Meta Muse Glimmer are great at "fill in the middle" of frontier architectures and plans. Frontier generated plenty of great context already to keep them on rails.

Delegating like a CEO down a pipeline of expensive experts to cheaper local small models could become a common trope, especially if Apple M7 and beyond live up to rumors as LLM tuned, and chip competition exists to keep forward progress, SaaS models are cooked.

The goal for chip corps too is the right mix of generic model enabling logic; not necessarily a full concrete model but enough of the abstract to efficiently boot strap and run a model; move common patterns to silicon not data.

Token vending is little more than behaving as a "wrapper app" over electricity. There is zero technical moat to their business.

True. We will end up getting more Google alternatives. Nothing beyond that for now at least.
> There is a lot of value from LLMs

Asking sincerely... apart from FOMO subscription revenue, what is the actual money-making proposition?

I don't know why nobody has said this yet, but...

The eventual logical move is that they build a completely reinvented AI-native operating system.

The funding they're getting gives them the resources to build and compete on a fundamental level, IMHO.

If you don't believe me, look at the recent demo where they had Fable 5.2 build an OS from scratch.

They are coming for the whole stack, my opinion.

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How would they make money from an operating system?
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i use llm for

- work: I need frontier, cost of mistake is huge - home: i do entire renovation with it, cost of mistake is big. monitor baby health, development, etc: cost of mistake is big , taxes: cost of mistake is big casual researches about certain facts, shopping, booking: cost of mistake is medium

non of this fits : i will run an expensive laptop hidden from the baby, since i'm on the move, there is a small percent of casual queries that normally will go into finish products: google ai, muse, etc.

The frontier is addictive.
> Yes, some frontier models are much better but users can still chose to use cheaper models for most of the work. In fact most applications, through which people will interact with LLMs anyway, will not need frontier models unless they offer "chat with AI"

I am finding some really routine tasks to be borderline with frontier models. Performing E2E testing of enterprise web apps would clearly disintegrate with local models. You need that reasoning black box on top. I don't care what your favorite benchmark says. I care about what actually fucking works.

The people who don't understand the economic situation are those who are in the pure play space with AI and multi agent circuses. Why bother spending any money when the occasional failure has literally no consequences? Who in their right mind would pre-pay for tokens?! I wish I could see the statistics on what % of HN uses AI for fun vs for work. It is clearly a kind of Factorio entertainment experience for a lot of people. If I was just using it for entertainment this whole IPO business would look really silly to me too.

We all love moats, but I mean, it is still possible to make money in an industry simply by being the best at what you do and charging for it.

Anthropic has shown a consistent ability to deliver the best general purpose models. Can that continue indefinitely? Will models become "good enough"? Will open weight models catch up to SOTA models? Will some genius start a new company with better models?

And, on Anthropic's side, will they be able to use their market power that comes from being the best to push through regulations that will create a moat; instituting some sort of mandatory safety checks that coincidentally are exactly what Claude is trained to pass, regulating the amount of compute or trying to claw back data centers to prevent new training, etc.

Or maybe they just have the magic sauce and they're going to stay on top of the game and people (like me) will be happy to continue paying money for their product.

It feels like people are still trying to bet on the horse that will achieve gAI.
I'm fascinated by exactly how an investment in the company that first reaches AGI (or whatever we decide to call it) might pay off... It feels like the stocks would absolutely be worth owning in the immediate term because they'd be hot property at the point where people realise it's happening.

The thing that I'm less clear on is, if and when they achieve some kind of recursive improvement exponential growth thingy, isn't that going to heavily disrupt the entire economy / stock market? In that environment, would Anthropic's stocks really be a good bet, given they have to operate within the economy?

> The thing that I'm less clear on is, if and when they achieve some kind of recursive improvement exponential growth thingy, isn't that going to heavily disrupt the entire economy / stock market? In that environment, would Anthropic's stocks really be a good bet, given they have to operate within the economy?

That's a long-term problem to be dealt with later, greed dictates to pursue the former as long as the music is playing and everyone is dancing. Similar to 2007-2008 when it was clear that things were breaking but the incentives were to play the game for as long as possible before it imploded.

It's clearer to me why this works for generic investors than for the AI companies themselves - unless their plan is just for key employees to cash out and live on a private moon just before Consequences arrive.
>> that first reaches AGI (or whatever we decide to call it) might pay off

It is a myth. They are chasing science fiction. They either dream of an omniscient overseer who will take control of society and nominate its shareholders-parents into the governing elite, or they envision a chatbot that will solve every problem, again turning shareholders into the power brokers. They forget that nobody will ever be allowed to "win capitalism" and take over the planet. Companies have are torn down for far far less. Every AI model is data, ones and zeros. It therefore can be copied/shared/leaked. Intellectual Property law is not a ladder for assent to lordship. It can and will be rewritten or outright ignored rather than allow capitalism to collapse.

“Yes, the planet got destroyed, but for a beautiful moment in time we created a lot of value for shareholders.”
> It feels like people are still trying to bet on the horse that will achieve gAI.

I think that at this point gAI is just a marketing blurb, and the actual race is to dominate current practical applications involving basic RAG and ReAct loops. This can go from anything between software development, business intelligence, and market research. A company whose top brass can use a team of agents to do what nowadays they assign to mid- and top-level management is an executive with tighter control over the whole business process. For this you don't need gAI.

I've noticed they've actually stopped harping on about this AGI nonsense, I suppose because no one was buying it to begin with and they themselves didn't really have any idea wtf they were talking about when talking about "AGI". Now it's all about a bajillion agents running autonomously or whatever
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Easily in the context of the corporate world is to pay for something, that something gets installed and then just works, and if it doesn’t work there’s always someone you can call 24/7 to come and fix it. I don’t see how this is possible with open models.
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100% - brace yourselves for enshittificarion.

I’ll always remember the good times.

But you’re wrong ser about small or cheaper models. Choosing to work or not having a choice to work with cheaper models means you work slower and more methodically because you have to plan out the work and size it to fit. This has huge implications on the value of the work you can produce as an employee or solo developer, and it’s a skill working with these SOTA models - there is specific crafting that must be done to be effective with each and their capabilities.

You will see the old eyeball real estate game, forcing more of your experience into their apps and platform so you can see ads or “new slop features”. You will see the SOTA models more closely guarded in an effort to bait you into that platform, and yes, you will see them doing things they never should be doing, moving towards an open AI like model where it can order a pizza, where monetization it was always important, but is now the golden rule, before all else.

I hope open models can at least give me opus 4.8 experience soon, I can work with that. But nothing out there today can do it and that terrifies me.

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> Anthropic and OpenAI will have to become more of the end user application stack. Files, calendars, emails, photos, and much more have to pass through them for them to keep making money. Else they cannot make money like the way they have been in this early era of LLMs.

...so, Google?

Without the advertising revenue. Yet.
What work do you find frontier models significantly better for?

I have been playing about with different models having started a new job recently, the medium priced ones don't seem any worse so far. Admittedly my tasks have been fairly straightforwards so far.

If they actually crack AGI, they're going to sell the results of using it, and not model access themselves.
I believe the models have been effectively commoditized. It's believed by many that the lead of the frontier models over open weight models is only 6-9 months. That was one of the pillars holding up the SpaceX/Anthropic/OpenAI valuations.

The other pillar is hardware but I think that's only going to last a few years at most.

These trillion dollar valuations were based on the idea of "winning" and "owning" AI (IMHO) and the open weight models have killed that outcome. Now it's a rush to cash out before it all comes tumbling back to Earth.

When people want to argue that AI is a commodity, they confuse two concepts

1. switching costs

2. fungibility

I do agree that LLMs have low switching costs. But they are not fungible - each model is unique with different strengths and weaknesses.

I also disagree that they can increase switching costs by moving in application stack.

For instance, oil and electricty are commodiites because they are fungible, not because switching cost is high.

Whereas clothing has low switching cost but not fungible

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>something that I can switch easily

something I find even easier is to never pay anything to the creators of the most inhumane, antagonistic skynet-tier chatbot ever

¯\_(ツ)_/¯

Not only can you switch easily, they all seem to do the same thing, fail in the same ways, make the same bad linguistic choices, write the same code... I think at the end of the day, LLMs are a commodity. They're like a grease, or oil. They're trying all the tricks with branding cute names, version numbers, benchmarks, thinking levels, but it all just seems the same stuff to me: I put in tokens, I get more tokens back, and if I didn't know ahead I wouldn't be able to distinguish if they'd come from Anthropic or OpenAI or wherever. Maybe some people can but I can't.