I'm not convinced raw costs matter:

1. Compute costs collapsed since the advent of Cloud and yet hyperscalers still have fat margins.

2. Many open source office suites exist yet none compete with the ubiquity of gsuite or office. GitHub, Slack are similar examples.

3. Both Windows and macOS dominate the home desktop space despite free alternatives existing for a long time.

4. Many formerly open source infrastructure components like Redis and Elastic Search have Apache equivalents, but they still command healthy margins.

I understand the arguments for a margin collapse, but I don't see any historical analogues. It seems that enterprises will pay top dollar for service guarantees, integration, and someone they can sue.

It's nobody gets fired for buying IBM all over again.

There's a huge case of survivorship bias when trying to recall historical analogues, because in every instance where margins collapsed and competition made the industry a commodity business, the big proprietary names are no longer with us. Here's a selection of examples, though:

1. Memory chip margins collapsed so much in the 80s that Intel exited the memory chip business entirely. At the time, they were known much more as a memory chip company than a microprocessor company.

2. Margins for high-end workstations collapsed in the face of cheaper IBM PC clones and an explosion of MS Windows software. This led directly to the deaths of SGI, Sun, Symbolics, Lucid, LMI, etc.

3. Proprietary UNIX variants like HP-UX, IRIX, AIX, and SCO Unix have basically completely died out, replaced by lower-cost proprietary OSes like Windows and MacOS, or by open-source descendants of Linux and BSD.

4. Many commercial database vendors like Oracle, dBase, Sybase, FoxPro, and Microsoft (SQL Server and Access) found themselves very much under margin pressure from PostGres, MySQL, and SQLite. Oracle survived thanks to their massive installed base and legal department, and Microsoft survived because they could cross-subsidize from their OS and Office monopolies, but dBase, Sybase, and FoxPro are no longer with us.

Unlike all your examples, switching out an LLM is both cheap an easy. So easy that every 3 months or so new models are released and people grab them and start using them.

The UX is the same regardless the provider. You send in a prompt, it spits back an answer.

In all your other cases, the cost to switch is losing support and a difficult transition period. But in the case of LLMs, there was no support to begin with. The transition is basically updating your current harnesses to know about the other models.

I think the comparison most apt is the rise of AMD. Sure, it never(?) achieved market dominance, but it did ultimately make a huge dent. And a big part of that was because AMD x86 was pretty close and pretty compatible with Intel x86 at a fraction of the cost.

They don't just need healthy margins, they need to make back almost a trillion dollars in a couple of years. Comparing that to elastic search and redis doesn't make much sense.

Hyperscalers work because it actually has value compared to free offerings and because of the absolutely massive cost of switching providers.

Similar with Windows and macOS. Extremely high cost of switching to something different, if possible at all.

Same with office. Extremely high cost of switching due to compatibility issues and retraining of staff.

Your post primarily shows: It's all about lock-in. So far, it doesn't look like LLMs have any of that. So I don't think your points are valid here at all.

> but I don't see any historical analogues.

The losers are quickly forgotten. Palm, Blackberry, AOL, MySpace. Yahoo, etc.

Software gets replaced all the time too, you even listed one and didn't realize. 15 years ago you'd call office irreplaceable, now you have to add gsuite to the mix, in 15 years there might be others. I know people that have never had office installed on their PC and use spreadsheets daily.

> It seems that enterprises will pay top dollar for service guarantees, integration, and someone they can sue.

Of course. But why pay $25 per million tokens for sonnet when you can pay $3 for GLM? Both probably running on AWS/Azure/Etc. under some third party.

Those solutions have moats:

1. the cloud moat is mostly around talent really. Try finding people who can self host the alternatives to S3 et al at the HA and the scale the businesses need. Those alternatives are usually not free either, and each product might have its creator acquired (and the product cancelled) or similar. if you're a larger business then the data lock in becomes a moat: getting your data out of the cloud is prohibitively expensive. Furthermore, large businesses have sweet discounts.

2. ms office has immense networking effects due to its formats being quasi standards in many industries. try sending an odt to a government entity. As for gsuite, it uses open formats but it's classical google fashion a large suite of software bundled together and not that expensive for what it offers.

3. Linux is not a free alternative if you're a business, you still need to pay someone to support the computers with linux on it, and operating systems have the strongest network effects ever. Linux also has no stable ABI so one can't easily deploy third party software for it.

What's the LLM moat? Codex is OSS and Claude has gazillions of alternatives. Cursor is a nice app but it's a bunch of patches on top of vscode, a team of 5 people can vibecode it in 6 months.

A lot of those things you mentioned have sticking power because they’re familiar to folks and migrating to something else is a big deal.

I can’t imagine most people would be able to tell the difference between Sonnet and GLM 5.2. If the infrastructure around the model you’re using doesn’t change, then swapping models is extremely easy.

In these examples cost of the solution does not generally scale with the use of the solution in the same way we see token use. In the case of LLMs the cost of use scales very differently than seat licensing.

Many corporations have found they have a new cost center drawing tens of millions or more with little direct evidence of productivity gain. Corporations are probably best positioned to either switch providers, leverage router solutions or at worst use the fact that they could to drive prices down from the proprietary providers.

The target audience is different. Coding is mainly a trade of the tech savvy, who like many on r/localllama users do not hesitate to deply on 16GB Vram gpus. Even if so, it is estimated that within 2 years we will be able to run Claude 4.8 on consumer hardware give the rate of improvement of open-weight LLMs, which will put more financial pressure on "paid" labs. It's just a matter of rate of improvement which is shrinking between open-closed models.

> I understand the arguments for a margin collapse, but I don't see any historical analogues. It seems that enterprises will pay top dollar for service guarantees, integration, and someone they can sue.

Intelligence has diminishing returns, the analogues are with humans. It's a waste to hire Albert Einstein for $X million to operate the cash register in a gas station.

Artificial super intelligence will not have many customers.

Hyper scalers have a decent margin from a small number of their services and a much more normal if not a loss from many others. Additionally a massive part of their profit is support services and contracts.

They also benefit from the fact that developers do what is convenient for themselves and not what is necessarily computationally efficient (i.e. not pay attention to cross AZ egress/ingress, run an apache spark job when it could be done all within a normal database, build their entire product on irreplaceable/unswappable cloud provider specific databases and storage solutions).

AI will also experience a significant margin collapse, it's just not clear who will eat the brunt of it yet, the AI companies themselves or companies like Nvidia as more chip manufacturers/designers come into the arena and can meaningfully compete.

To switch an LLM you just need to open another browser tab and type in your chat query. You cannot say the same for any other kind of software. Traditional software have a large switching cost which acts as a barrier.

LLM providers are like airlines. You only need when you have travel and most of the time you go for the cheapest one. Maybe LLM providers should start providing reward points :) .

The flaw is here:

> 1. Compute costs collapsed since the advent of Cloud and yet hyperscalers still have fat margins.

Cloud opposes switch inertia. To setup a complex system in a different environment is a complex operation. Changing AI provider is switching an endpoint.

Nobody got fired for IBM, but it took some battles for IBM to reach that level. Same with AI. Brand images won't develop until the street battles are over and dust settled. Otherwise, Google wouldn't have taken over Yahoo and ChatGPT would have remained the king. That didn't happen. The street fights are still raging in AI and won't settle down any time soon. Cost-concious usage can kick-out Anthropic overnight. Ultimately it's only the cost that matters and that will blunt all other factors, including security concerns and risk aversion etc.

Also, note that even the highly-regulated sectors invited opensource products and services and allowed data transfer across their network perimeter. That required "blunting" of the security policies, and it did happen.

> 4. Many formerly open source infrastructure components like Redis and Elastic Search have Apache equivalents, but they still command healthy margins.

Elastic just had round of layoffs[1]. Elastic still runs operating losses till Q1 2026 [2], albeit a small one, however just breaking even in operating income is hardly "healthy margins". A P/E of 17 is not exactly signaling confidence given they are growing ~20% y-o-y.

[1] https://www.elastic.co/blog/ceo-ash-kulkarni-announcement-to...

[2] https://ir.elastic.co/News--Events/news/news-details/2025/El...

Raw cloud computing costs have a fairly small margin over what they could be. Nobody with real purchasing power is paying anywhere near the listed retail rates. It's part of the reason smaller providers e.g. OVH, can remain quite competitive.

The other items have very strong lock-in and capture ecosytems. Microsoft Office is the first and only office suite anyone uses and its cheap enough for nobody to consider a real alternative. Microsoft could attempt to charge $10,000 a seat and while some will certainly stay, others would look for an alternative. But for just $10 a month, its a fair price to pay.

I suspect the concern is that model serving is a stateless “simple” problem.

As yet, no one has identified a reliable moat in inference. If the moat is performance, then prices will collapse. Unlike traditional cloud moats around state, operations, and capex management - I can host a model reliably with less than 30 minutes effort.

The point in the article that you are not considering is how easy it is to switch to a different model provider right now.

You literally change a couple of env variables and you are done, your user experience is basically the same. I can try new models for an hour and be sure I can go back to the original model as quickly if I want.

That is not the case for the software you talked about. They all require way higher switching effort with more perceived risk.

1,2,3 are dominated by platform stickness or even active lock-in.

Can't say I see the same advantages to stop you switching the model you use.

> It seems that enterprises will pay top dollar for service guarantees, integration, and someone they can sue.

Sure. Though it does depend on whether you need regular updates. If you want the model to be aware of the latest research - then fine. However it already does the job, you might prioritize stability over constant change.

> It's nobody gets fired for buying IBM all over again.

Except they when they did when IBM was no longer good value for money.

> but I don't see any historical analogues

None at all? You mentioned IBM - who is using AIX on IBM hardware in 2026? Who is using Solaris on Sun hardware? It's pretty much all gone to linux on commodity hardware.

Remember Netscape - thew browser company? Killed by Microsoft bundling of IE. How hard would it be for Apple to bundle GLM based services?

I don't think the parallels are quite as clear for a few reasons:

1. Lock in - with an LLM, there is practically no lock in because of the inputs & outputs being text. You can move easily

2. Motivation - I think you underestimate just how high some of these bills are for companies. Finance departments are already getting mandates to reign in spending even at the high level of subsidization.

3. Political Meddling - we're now at the point where the US strategy seems to be to artificially limit access to powerful models. If China continues its trajectory they will have models as good as Fable in 6 months to a year, and they won't lock it off. So cheaper, better models that are available is a massive incentive to switch. China is much less motivated to ratchet prices up if it's winning them marketshare. I do think David Sacks + AI strategy for US Gov are being very short sighted and it's going to blow up in their faces.

> It's nobody gets fired for buying IBM all over again.

I think that's the historical analogue. How is IBM doing compared to pre-personal-computer disruption? Initially-limited home OSes like DOS were good enough to eventually dominate business too. The AI labs, with their massive funding and spending, are speedrunning the whole thing in a way that just might make that disruption faster and more fatal vs the lingering zombie relying on the IBM name. (The more massive amounts of capital you raise on future speculation of enormouse TAMs before, say, becoming profitable, the more dependent you are on the future speculations of outside interests. Double-edged sword.)

And I don't think being suspicious of the future of OpenAI margins is the same as saying open source DIY will dominate at all.

People don't wanna install their own OS or deal with changes in their office suite or rack their own servers, but a low-cost AI provider is gonna be more like a Wikipedia-vs-Encarta situation in terms of accessibility and similarity-of-interface.

When a hyperscaler is viewed as a software company their stock and value multiplier is much higher than if they are viewed as a commodity with expensive infrastructure costs. There is now not enough compute resources to serve demand. It requires sustained capital to grow compute resources. The costs are uncollapsing due to the overall demand plus the pressure of LLMs. Capital costs matter.

Examples two and three largely persist due to massive vendor lock in after the vendor has done enough work to capture market share, but that does not seem to be the case for AI labs to my knowledge

> Many open source office suites exist yet none compete with the ubiquity of gsuite or office

I think this is more about collaboration being hard to solve. Without collaboration gsuite/office offer nothing.

> 3. Both Windows and macOS dominate the home desktop space despite free alternatives existing for a long time.

Mac OS is free too, just free as in beer.

> It seems that enterprises will pay top dollar for service guarantees, integration, and someone they can sue.

In the grand scheme of things, american enterprise is filthy, filthy, filthy rich. I wouldn't imagine they're the best example of rational spenders.

There’s actually a strong case that agents will erode cloud providers’ margins because the lock in migration cost will be much lower in the future. No one ever migrated before because you’d spend $$$ to save $$ then the new vendor would gradually raise your rates negating the savings.

They may pay top dollar but there's all sorts of evidence that they'd very much like to pay radically fewer top dollars than the unsubsidised, off-plan price.

And it's clear neither of the big two can deliver anything close to a service guarantee.

People might not want to be on update treadmill of proprietary weight models, for enterprise things. Things change a lot between models and they can't guarantee backwards compatibility like you can for deterministic software

. It seems that enterprises will pay top dollar for service guarantees, integration, and someone they can sue.

Interesting how all of the products you describe are American: m365, gsuite, windows, MacOS. It's not just about having someone to sue. You could sue collabora and canonical but they're not American. Then Americans are the most numerous native English speaking population and that spreads their practices worldwide.

The biggest difference between the cloud and AI is that an AWS server might cost 10x of what you would pay for if you bought your own, the overall expenditure is still just a small fraction of the company budget.

In contrast, even companies who spend hundreds of thousands per employee feel the AI spend right now might be too much.

> 1. Compute costs collapsed since the advent of Cloud and yet hyperscalers still have fat margins.

No, compute costs collapsed (before mid-2025) because of normal technological progress on all fronts of compute.

Operating systems and office suites (like windows and word) have big network effects and high switching costs.

Much less with llm chatbots/coding tools.

good observation! however, I'd argue it's the distribution channel and installation friction did the job in the cases you mentioned.

given how easy it's to replace LLM API in claude code, and how easy it is to write a claude code clone with itself (Fable is pretty good!), the collapse is coming.

Remember web browsers? compilers? web servers? databases? windows embedded? server operating systems?

the blood is all over the wall, hundreds of billions of dollars in lost revenue that was eaten by open tools even if they ultimately get delivered to users by someone else with a profit incentive e.g. AWS selling deployment of OSS

1. their margins don't come from service guarantees (see github), they come from unlawful anti-competitive behavior which is likely to be prosecuted under future US administrations

2. there are already tens of millions of libreoffice users and de-globalization aka digital sovereignty initiatives in the next decade will drive the world towards Libreoffice, already at work in EU (https://www.zdnet.com/article/why-denmark-is-dumping-microso... https://cybernews.com/tech/germany-microsoft-word/

2a. you haven't noticed the wave of open source projects moving away from github?

3. Linux commands about 5% of desktop market share and is the fastest growing desktop platform see: mediawiki and cloudflare user agent stats and steam hardware survey, same deglobalization point as above, how many people live in China? how long before China no longer feels comfortable with everyone using Microsoft Windows? What OS will Chinese people/corps use instead? hint: https://en.wikipedia.org/wiki/Deepin

> I understand the arguments for a margin collapse, but I don't see any historical analogues.

How is this the top comment? It lists all the outliers and ignores thousands of instances where fat margins caused a collapse.

I mean, just what Linux did to the dozen or so fat-margin unix server companies is already a longer list of collapsed companies than provided in this comment.

AI costs a lot more than all these, combined.

You missed two things one, a consist thread across all your examples - every market ends with a duopoly along with smaller competitors and two, which of these industries started with multiple billion dollars companies competing with each other?

Even if your case is that two companies in the AI group are going to survive and those will have healthy margins, others are going to suffer and compete on price. So saying “AI margins are going to suffer” is a fair industry wide statement. Maybe it’s not Anthropic or OpenAI or whoever you are thinking of but surely for Gemini or xAI etc?

The same critique of those points can be made which was in the article. The cost of switching is minimal.

This isn't SAP or a CRM or some other business where workflow = moat.

I think the big thing here is that paying high margins on a relatively small expense is much more palatable than high margins on a big expense. If a company is spending $1 billion/yr on tokens that a really big incentive to find an alternative where spending $1 million/yr on some SaaS with even higher margins can feel like an easy choice.

For 2 and 3, office software and OSs have strong network effects and up-stack effects, just like CPU instruction sets.

Also, I'm sorry, but OSS office suites compete with Office and GSuite the way grocery store frozen pizza competes with Domino's and Papa John's. Quality and completeness of execution matter a lot in that category.

Cost is a measure of scarcity

Once something is abundant, it's hard to justify extracting big margins from it

Which is why so much effort goes into manufacturing scarcity instead

We will keep using Claude because internal choices made by engineers and internal gatekeeping by engineers make everything else unfeasible, and going back on that would require said engineers to admit that they did something stupid, so it's not likely to happen.

> It seems that enterprises will pay top dollar for service guarantees, integration, and someone they can sue.

Sure, but those are all things that can be trivially provided by a large inference company. In fact, I’d trust an AWS or Cerebras contract provisioning an open model before I’d trust an Anthropic or OpenAI one.

GitHub, Slack, and Office have network effects and transition costs.

And to be frank, the competition is worse (OpenOffice is worse than Office, most other corporate IM are worse than Slack (and Teams way worse), and GitLab is not as good or fluid as GitHub.

All the more reason to focus on those service guarantees, integration, and lawyers while making the underlying model easily swappable to whoever’s winning the frontier model involution battle at the moment

I don't disagree with your conclusions (enterprises will pay top dollar for service guarantees, integration, and someone they can sue) but by that same logic there is no clear winner with Anthropic/OpenAI. Claude has a habit of going down on me when I need it most and seems to be struggling to even keep 3 nines of availability. They're actively hostile to integration and seem more convinced they should be suing others than behaving in a way that doesn't get them sued.

That's not to say I don't believe that there won't be a closed source correlate. I just don't know if OAI and Ant are all that exists.

there's huge margins on GPU time, not tokens.

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