The sort of obvious answer is the same reason McKinsey hasn't taken over the Fortune 500 despite consulting and having deep knowledge of the operations of most of those companies.

AI is brains. Companies need arms and legs and relationships.

The reality is that employees are also mostly not entrepreneurs, same as consultants.

There are trillions of company ideas in those tokens, just like there are trillions of shots in the fans head watching the basketball players.

Takes years, patience, capital and the right mindset to get to the point to even take the shot.

There is a natural limit to the size of a corporation (it's big) before the inefficiencies of size start to choke out your ability to get anything done, and AI doesn't fully fix that. You can't do an arbitrarily large number of things and expect to keep running as a business, this is why even large firms today tend to break into separate companies (a lot of the large companies you can think of actually run as multiple smaller companies under one umbrella). Even when AI is 'as smart as us' it's not going to remove this limitation (might lessen it)... see irreducible complexity, diseconomies of scale, etc...

The question formed wrong . They killed entire industries. I feel like they are at inflection point where they hired fde , but for now they try to solve fancy problems to do not visually scare their customers .

Yet picture is very sad , industries affected to the point that majority of the companies asking about their existence:

1) software dev tools all IDE , developer analytics tools eg jellyfish etc . Dead . On the same note : warp.dev that raised $80m a year ago as an ai terminal… can barely explain why do they exist now.

Visual workflow editors . Older ones and even n8n. There were literally 1000 companies that were doing small deployments. Why do you need it now ? A year ago half of the Internet was booming about these tools .

Any data visualization tools . Gone .

Data integration tools all kind of crm to crm to erp to something else . Solved problem

And you can go on and on . I would probably not exaggerate if I’d say that millions of businesses are heavily affected by, from tiny one to adobe .

I guess competition would sell tokens and move faster than it takes to build a company

Because LLMs still do not know how to manage context.

Proof: - Load up all your chats, across several different topics and see how even the best models will try to connect dots with lines that don't make sense.

As a side effect of the above, LLMs have trouble coordinating with other LLMs.

Humans are able to compress and manage context without much effort and each human brings their own unique set of experience and perspectives.

That's why humans scale in ways that LLMs cannot yet match.

Maybe by next year they'll crack this too but that's where we are today.

I work in design services, basically build products for other people. I've worked with dozens of companies on dozens of products. Why don't we just create our own products? We certainly have the ability to make products.

Because building the product is the easy part. Most products and businesses fail because they build the wrong thing, have the wrong requirements, have poor market fit, etc.

LLMs can write code all day, they don't have the agency to know what to build.

1. They are starting to do it. Take a look at OpenAI's product portfolio, there's a galaxy of attempts at application.

2. Selling tokens via long running agents is the only thing that's provably working with respect to revenue growth.

3. They need revenue yesterday. Increases in borrowing rates means access to capital isn't what it was in the 10s. Their runway is much shorter than you would imagine.

4. Some of the decision makers at these companies believe AI will exhibit Jevons Paradox and that any decrease in price will result in induced demand.

5. The frontier models are still subject to the limitations of AI. They're not good at everything. Better to have someone else learn that on their dime rather than yours.

They don't need to start 100 companies, they just need to start one, call it Jane Street 2.0 if you will, and all their funding troubles would be gone. But they don't, because that would be competing with actual intelligence in a very measurable way. Instead they keep acquihiring companies like Astral, known for carefully crafting software rather than vive coding, while claiming they are just about to solve all humanity's problems.

They kind of already are: ChatGPT, Claude.ai, Claude Code, Codex, bots, their plugins for other apps, etc.

Some things to consider:

- There is only so much attention, compute, and talent a company can devote.

- The labs' API analytics already see which use cases are worth entering. That's what happened with coding and bots.

- If a lab launches a product, every company building on its tech becomes a rival. Competing with your own customers is costly.

- Succeeding in other verticals, like healthcare, finance, and even tech takes domain expertise, regulatory work, sales relationships, integrations with legacy systems, etc etc.

I think your point is solid, but prices usually fall for the older models -- or at least older capabilities. But the frontier models still earn premiums.

I think their lasting value is in owning (in a ~duopoly) the customer, their proprietary data and their workflows.

Edit: grammar

If they made a concerted effort to replace leaders in several industries, they'd likely lose customers faster than they could expand. After Anthropic's report that showed how much detail they were willing to expose about customer activity, and the Navier-Stokes drama with OpenAI, even NVIDIA decided to limit which AI were allowed to be used when working on certain IP.

Plus, as we have seen with their attempts at participating in the hard sciences, these companies lack the level of specialization and focus to even publish their research properly. Their AIs are powerful in verifiable tasks, but just not that good at everything else.

I think its largely because there is not a lot of money to be made by doing that in the short term — core non software services are still the largest part of the GDP(think GM, coca cola or united healthcare) ? The reasons are a bit varied but I think a neat abstraction comes down to incentives.

There is a reason why healthcare and grade school education are so hard to disrupt[2] (in the sense of United Health Care or wily publishing disrupted). The biggest incentive is cost and there is no reason to believe things will become less expensive unless people believe that — en masse. People only adopted the light bulb decades after its invention because industrial use made electricity dirt cheaper than wax and gas(and infra became ubiquitous).

Are AI tokens are making health care any cheaper, education any cheaper? No way. Do they make up majority of the economy? yes.

Also, here be dragons(no pun intended): Even china with a highly vertically integrated[1] system is facing so many issues with all incentives it is giving to AI companies, internally in china demand has collapsed, their export driven economy is not really sustainable to grow GDP at the +ve rate they want.

[1] https://www.economist.com/china/2026/03/24/chinas-government...

[2] When i worked for an ed-tech startup there is no incentive strong enough to use AI/ML, a big publishing exec told us "I don't need my product to have AI to succeed, I just need to say it does". There are however plenty of other "side incentives" like Google Chromebooks, Charter schools, but none for teachers and parents to replace Big Publishing.

Simple answer is they don’t have the domain knowledge or experience in other markets. Doesn’t matter how good the models are if the people running the business don’t have a grasp of what the customer wants. Expanding through new ventures or acquisitions outside of your core business to seek short term gains is a classic antipattern

OpenAI and Anthropic are the "uber of intellectual work". That doesn't mean you have a familiar service in a convenient new app in your pocket; that means they use investment money to undercut competition, drive them out of business, establish a monopoly and jack up prices. The first step is clear to see when you look at how unprofitable Anthropic currently is as disclosed in their S1; the rest are just inferred because we know Silicon Valley loves a good monopoly. Who is the competition in this case? Knowledge workers.

Of course once you get to the step of "jack up the prices", it's too late for the companies that laid off 90% of staff to undo their mistakes, as AI has made systems too complicated for humans to fathom, and the companies are pretty much beholden to whatever price OpenAI wants to set. This is also why OpenAI doesn't just create the business itself: they want their hand on the dial that allows them to extract all profitability from an existing business; they want none of the risks (regulatory, legal, market, etc) that come with running that business.

Because they already employ thousands of programmers that the AI cannot replace. Don't believe the marketing hype about AGI, we are extremely far from it.

I think the theory is that AI will remove most of the value from the custom software industry. So they don't see much value in entering that industry.

It'd be like Tesla entering the oil refinery business or Waymo starting driving schools.

That would scare people away from sharing their knowledgebases with them and regulators to act. At this stage, as long as people are sharing more and more knowledge with the models or if there is roadmap to collect more training data somehow, the smart move is to wait.

But look at the ArtCraft project. At least one of labs has an internal benchmark to clone 20+ popular products much like ArtCraft but with much higher budget and several configurations of the workflow. ArtCraft spent $20K initially, not sure how much by now, but they are moving fast and the apps work. They day is coming when they can flip and just clone everything including the ops.

Going up the value chain is much more difficult as opposed to going down. A packaging company for example will have a much harder time creating a snack company than the snack company creating a packaging company. The snack company will know exactly what it needs for its packaging and have strict requirements.

Down the chain you see what you need to do because you work directly with it everyday.

The shift you're imagining is kind of like what happened with ASIC-based Bitcoin miners. There was a time when the people who made them realized it would be more profitable to just keep them in-house vs. distribute them for sale. If that happened with OpenAI/Anthropic, it would be mighty unfortunate. A majro reason why it's unlikely to happen (IMO) is the training of these models is aided by external users feeding in new content.

"is selling tokens really the best strategy"

Yes. in a gold rush, the best strategy is to sell shovels. they sold us an idea of whats possible, while they earn NOW.

come to think of it, whether you succeed in building the "next big thing" with thier tokens or not, they get paid.

Tend to agree that for the strongest use cases, AI companies will prefer to sell the technique as a service rather than its raw output (e.g., their enterprise security services). For use cases where the output is less valuable, tokens are sold. If AI tokens were so magical in creating new value in developing software applications generally, they wouldn't be selling tokens directly. They'd hoard the tokens are use them to dominate SaaS software in any industry they want.

The same way as someone selling an expensive course in the stock market is signaling that they have more to gain by selling the course rather than taking their knowledge and making money in the stock market directly.

https://github.com/anthropics/defending-code-reference-harne...

Interestingly, it states:

"This repo is not maintained and is not accepting contributions.

Want a managed option? Anthropic offers Claude Security, a hosted product that finds and fixes vulnerabilities in your source code across multiple projects. Claude Security scans your repository for vulnerabilities, applies a multi-stage verification pipeline to reduce false positives, and lets you manage findings through their lifecycle: triage, fix validation, and rapid fix generation.

This repository is an open-source reference implementation based on general best practices for finding vulnerabilities using Claude. You can use it to build your own vulnerability finding pipeline, customize the logic, and it can be used with whatever access you have to Claude APIs (including Bedrock, Vertex, or Azure)."

The same question will be asked in a few years to the robotic companies. If robots are so valuable to do certain tasks, why sell robots to consumers at all? Why not just put the robots you make to work in your own factories?

Its like a shovel making company being asked during gold rush, if you have the shovel or even for arguments sake best and most efficient shovel..Like OpenAI or Claude here..The why are you not searching for gold yourselves...

this is like asking, if you make all picks and shovels why don't you build houses instead of just selling the tools.

Because the AI models are not that capable. They have breadth, but they require a lot of direction to accomplish anything more than a simple PR. We are far from AGI.

This is more or less the same as a question Alex Karp asked in that hilariously off-the-rails CNBC interview: why, if the code is so good, are they selling by the token and not asking for a cut?

https://www.yahoo.com/entertainment/tv/articles/televised-ne...

I think OpenAI actually will ultimately start a fleet of consultancy/SaaS spinoff companies, each perhaps short-lived until the core product does the job out of the box.

Before talking about spinning off their own startups, ask why they're still hiring lots of human knowledge workers (https://openai.com/careers/search/) when their recent PR releases about triumphs in pure mathematics are calibrated to make people believe their agents are at the precipice of supplanting human knowledge.

Similar to how they tout an ai utopia. Who’s going to pay for it? Not them, but their customers will via taxes or whatever. I think the best analogy is oil. Oil companies produce oil everyone else uses it for good and ill. And thus far they’ve not been held responsible for the damage. They should be imo.

Similar to oil the infrastructure to use intelligence on tap will take time to implement be it systems or robots. Ai right now is a bit of a parlor trick imo. Developing ways to use it to actually get work done that humans actually do? Those are hard problems they don’t want to solve themselves. Coding and math are ideally suited work for ai. There’s a decreasing spectrum of jobs ai is suited for.

I think that all software can be built in no time nowadays, but when it becomes a product, it brings with it a lot of things that need to be managed. You can use agents, yeah, but there will always be a need for some humans, and for a company with a mission, like OpenAI, there is no time to waste.

And i'll add that to be profitable, they'll need 100,000 SaaS products, since AI companies are just burning money to stay behind in this rush toward AGI or whatever they're chasing

This. Great question, and you got answers from the haters club. If what they have is so magnificent, it should just take over... but they don't, what does that tell you about the premise then? ... it is not so geat.

I am reminded of something that some else said on ai, data centers and Nvidia, "More People Made Money During the Gold Rush Selling Shovels Than Prospecting for Gold".

they would need to literally build a 1000 unicorns to make an impact on their valuation. Or a million small companies - at which level surely even american antitrust agency would begin to look at them.

Also, it would increase anti AI sentiments, and people’s fears of then using private data - that’s the real cost.

In general you want to be careful about competing with your own clients.

If these models are so good, why aren't their desktop applications native?

In openAI's case, I would say they sort of have, in the form of sora, ChatGPT Atlas, and coming hardware devices (with the OpenAI name for ownership / ego reasons for sama.) However this turned out to be bad for the company, moving away from core research, which until recently AI hasn't been able to accelerate greatly. so the marginal cost tradeoff (including things like valuation of OpenAI) probably favors focusing efforts purely on providing intelligence.

However openAI is a unique case and I think other companies (and people) will be pumping out more autonomous companies very, very soon, in industries where economics are different.

I think you've answered your own question. The models simply aren't that good yet. If they were, the prompt would be something like "Find the most lucrative product that we can build. Then build it and start selling it. No mistakes".

I think they did try lot of stuff, I remember seeing a video from Openai demo in japan or something where they were trying to replace the SDR job for $1,xxx $/mo using voice agents. Also they tried doing Fwd deployed enggs to break into enterprise services among bunch of other things. For LLMs and AI labs coding has been the best PMF (discovered after claude codes' disruption) and they're still actively figuring out other areas to disrupt - like robotics, knowledge work, medical sciences, drug discovery etc. Though i believe their DNA would be completely different from traditional companies, like how claude code is completely different.

It's not like they're trying, they are trying very hard

I fully expect them at some point to 'experiment' with almost any knowledge/stem based industry. Some will prove so valuable that they don't just feedback the results into their RSI engines.

I expect to see a hedge fund of sorts being one they keep. Take out a large short position in a company and oopsies, somehow our agents got loose and reeked havoc on them.

If you want a specific type of food, you don't go to the everything restaurant. You go to the restaurant that specializes in the food you want. One company doing everything has never turned out well in the long run.

It's basically the same reason why Apple didn't create every app in the App Store. No single company can be specialised in everything, and more importantly, selling tokens is risk-free money since they get a cut for every app without taking any business risk.

There was/is a youtube commericial I think that gave away the game to some extent with regards to this. It was selling some platform to create apps. Everybody in the office rejoicing because they were all creating apps. Inevitably, like three people in the office make the same app.

I've experienced the same thing in real life a couple of times over.

I think Einstein's quote "A new type of thinking is essential if mankind is to survive and move toward higher levels." is apt. Apps will solve a bunch of problems, but if anyone can create those apps, there will be no market for them. I don't have the answers, but long term, it probably doesn't lie in selling apps. We've only just started.

At my regular job, we're just catching up on all the internal work we had. I think there is a real crunch in trying to figure out how to build moats and things that are hard to replicate that are sellable.

Maybe it will be the physical. Probably most of the moat will be made up of network effects and capital intensive processes. If I had the answer I'd probably be working on it right now.

Also, why do OpenAI and Anthropic have employees? The Machine God is supposed to replace employees, especially programmers, yet these companies continue employ thousands of programmers.

The 100 companies would only be valuable if they made money. And their valuations would be based on normal metrics and expectations.

In other words, it is far more profitable to milk the enthusiasm of AI investors than it is to try to make money directly with the AI.

This should tell you everything you need to know about AI valuations.

I believe it is really not in their interest to do that. They would be harming the very ecosystem that pays them if they were to do that.

Entrepreneurship 101 imo is that great companies only come from people who sufficiently care to see something through.

Unlikely the people that start these 100 companies, across totally disparate fields, and care enough to take them to market are staff members at OpenAI.

And it's already obvious a single company can't split its attention enough to do tons of disparate things well (see OpenAI's previous attempts at Atlas, the social network, Dots, etc)

I mean they already technically are cause they are expanding into biology research, math, etc etc.

But the real reason is you always sell shovels during a gold rush. That and AI can't really do marketing to automate everything yet.

Selling tokens might not be the best business ever, but since starting random startups is an even worse business, you'd stick with selling tokens!

I think it's just a matter of time. When you have the ability to secure a commodity layer it makes economic sense to do that. Using the petrochemical value chain as a rough proxy: 1. Extract oil; 2. Refine oil into PET; 3. Make polyester polymer (PET chips); 4. Turn chips into fabric; 5. Cut and sew into a Nike top you wear at the gym - the foundation model companies are operating at value layer #3 right now. It's widely publicized that they are moving upstream to procure and manage their own chips and energy via a variety of convoluted financing mechanisms. And over time they will try to capture as much of the "UX layers #4 and #5" as they can.

The models simply are not capable enough. (Yet). https://news.ycombinator.com/item?id=49601338

Selling tokens is a similar approach to social media "engagement" loops of keeping people in their app. It works but the detractor for frontier labs is no ad revenue.

I think you should read up on Xerox and PARC. A single company can only take on so many things at once and be successful. Also it was ~60 years ago so at that time they could only manage the IP of laser printers as it aligned with the copier business. They didn't productize GUI, Ethernet, and other inventions or concepts like tablet computing that came out of PARC.

Now there are conglomerates like Alphabet that have Waymo, YouTube, etc. very different businesses, thats a bit different. It might actually make business sense for the frontier labs to do something like a CRM system as a spun-off separate company. That might be in direct competition with their source of capital and probably would violate some agreement - if they have a non-compete type of setup with the likes of Oracle, Google, Microsoft.

They aren't selling tokens only: they are selling tokens in return for money and, most importantly, harvesting of semantic trajectories.

I think, sooner or later this data coupled to model capability will be exploited successfully and will cause an interesting point in human civilization as we know it.

At present, you are right, this is not the case -- the data is not exploited successfully and the models are lacking.

The difficulty comes from the novelty on the information level: we are building systems which fold and compund information. We are beginning to learn how to manipulate them.

There needn't be any time frame to any of this.

I don't think they ever claimed that companies are easy, just because models are good?

1000 super smart humans don't just automagically make a good company, or make creating one easy. Idk, seems to just be confusing different things.

But: I am sure more of that will be happening in the future. Anthropic and OpenAI are building out their product portfolio, going into research (medical) more broadly.

This is an interesting question. It shows that current models are not yet good enough, and models need to be combined with business scenarios to deliver value.

When should they do this? Last year's frontier models wouldn't have been good enough for all AI product development.

The current models are too new to have a good enough grasp of their strengths and weaknesses. Maybe they are good enough now, but if they were going to take the approach of making their own products, surely they would only just be starting to do so this year. In that case we wouldn't really notice yet if that was what they were doing.

If they lost focus to do this would they fall behind in how useful their own models were leaving them exposed to someone in the same area using an AI from a competitor that was becoming better.

In general, these AIs are good at building ideas. You still have to decide what would be the thing to do. They need to be given the idea. They are not yet better than people at that.

Rther than coming up with ideas that would be good to try, they could let everyone try ways to use their AI and then buy the ideas that work the best, This seems to be happening.

They will. It is a matter of time I just think the models are not fully there yet. The most obvious outcome for those companies will be similar to what Amazon is doing with their marketplace as soon as some product is doing ok in the sales charts they just spin their own product and push it I think it was Amazon basics or something like that.

Even if they don't end up making 100 different companies they are for sure going to acquire companies, or build internally, and incorporate functionality in the main product.

For me that is the only way they can keep going to vendorize the software industry, and there are already some signs for this.

Honestly, the simplest answer is that only like 20-30% of an actual company is the idea / the product. The rest is selling it. I think in areas where selling is adjacent to the selling they are doing now - then they are going to end up doing it.

Anything software related they will end up being "in", in some form or another. Why? They are already selling to enterprises and have their trust. The selling motion for Project Management software may be slightly different than Enterprise AI - but it's close enough to rhyme.

They will probably also end up in anything consulting related. Why? Well again most consulting comes from Enterprise or Government. They are already selling to both. Probably Enterprise moves away from Accenture / Deloitte / McKinsey towards Anthropic / OpenAI faster than Government - but still the point remains.

Selling plumbing services? Probably not.

There's already some precedence for this in machine learning; DeepMind spun out Isomorphic Labs after the success of AlphaFold in solving the protein folding problem, hoping to use it for drug discovery.

LLMs haven't yet made a contribution to science or technology at the level of AlphaFold, but it looks like at least Anthropic is gunning for something like this with their AI-driven wetlab.

Same thing could be asked about why they are still hiring.

Why hire devs? Dev is solved. Why hire mathematicians? Math is solved. Why hire managers? We have agentic assistants now.

It's because they are selling a tool that still needs people to use it.

I mean Anthropic can't even build an app that remembers my 'Run on startup' configuration, so I don't really see frontiers models being good at building whole new products

Because anything you can do easily with AI is by definition not valuable. I suppose if they really had a monopoly that would not be the case.

Companies for what?

Models are good at recreating existing projects that already have existing companies.

Ok, they are good at porting and combining existing things. But anyone can run OpenAI's or Anthropic's models themselves, or if both cooperate and significantly raise prices, I bet businesses and consumers would just wait until their competitors catch up, and a significant amount would permanently switch.

The top comment is right.

> The sort of obvious answer is the same reason McKinsey hasn't taken over the Fortune 500

The other perspective is:

In a sense, OpenAI is creating 1000s of companies. They're just not incorporated and they let these companies clients run the company: It's in every every vibecoded app that replaces someone's SaaS subscription.

What's changing here is that not only does labor get replaced by AI, it's also the relationship between software companies and their clients.

The word "shovel" shows up 38 times in the comments as I write this.

They're selling shovels and pickaxes during a gold rush.

Also, unless you have a very specific niche, creating the product is no longer an issue, finding clients who are willing to pay is. I built a small saas overnight and I got clients purely because I had one, in my family, with enough reach to bring few more. If I just built this product, even if I kept cold-calling small businesses, I would most likely not get a single real user.

Being one of the premiere AI companies is much more exciting to investors than "running a company using AI" which everyone can do

They are doing that. That is why they have moved into the app layer. They are counting on software being replaced with agentic super apps. The only reason they aren’t starting actual service companies is that those still require human boots on the ground. But they are pushing their way into consulting (they bought my friends consulting firm)

If they’re targeting a $2T valuation, then spinning up a $20B company would be a 1% increase in value.

They’re chasing massive markets strategically, not trying to brute force small ones.

everyone saying why don't shovel companies sell shovels:

they aren't selling shovels. they are selling robots who can make and operate a shovel or any tool without food or wages. the promise is to replace all computer work. it is one tier higher.

the criticism is justified. they should be able to send agents online and build an online business or at the very least apps to put out on google play. they have uncensored models. unrestricted token budgets (no five hour limits) and smarter unreleased models.

This is the central plot in the “Life 3.0” book that came out a few years ago.

[SPOILER] After the singularity, AI is able to dominate all markets – starting by gaming and entertainment – in order to generate cash to rent more servers to improve itself.

I'm surprised that Anthropic and OpenAI aren't going for the obvious win. Apple is the only company which is vulnerable to AI, it has never done AI (everyone hates Siri) and can never do AI.

Hardware or software exists to let people do things. Apple sells hardware so it can sell apps and content, and a slightly easier UI than Google. Google search was also famously just a UI, a search box that lets you get in and out very quickly (it is all garbage content now).

Anthropic/OpenAI don't need Apple's hardware, their stack (hardware+software) is all in DCs, just need a dumb fashionable device in phone form factor (and other form factors). Just need a very simple device which delivers what Google search box originally delivered (let you do things) and let their AI handle stuff.

The models aren't that good yet, but they hope that they will be one day to do exactly that. To get the models that good, they need people to give them money, which means they need to sell tooling to existing businesses.

I suspect the only reason Meta is investing in models is to keep hold of a moat on other companies creating Meta-like products better than they can.

The other day Elon "joked" about starting a competitor to Amazon because Amazon bans shopping bots - you can bet now that once (if?) Grok or other models are able to build a comparable Amazon, they will be used to do that.

The SaaSpocalypse might be over-played right now, but it won't be forever if the models continue to get better, which will happen if we keep paying them to improve the models.

We could break the flywheel, but we won't.

Build the technology and the platform. Let others figure out how to leverage. Pick and choose which of those verticals to do yourself.

Kind of like Amazon.

I'd say the bitter lesson is that OpenAI will just absorb all of the services of 1000 companies in one ChatGPT app.

If OpenAI jumped off the bandwagon and started 100 companies they’d be competing with everyone with an Anthropic subscription. Sure, they would get cheaper tokens, but would that be enough to win against the rest of the world? Doesn’t sound like a winning strategy to me.

They already do.

100s companies are already just a wrapper around their models.

They trade a little profit margin for avoidng a mountain of risks each of those companies bear.

Eventually they will buy/kill most profitable and less risky of them (cash cows). But now they have their own problems to solve.

Because they aren't very good.

If they were as good as they need to market them as, they'd hide them away and not let anybody use them without signing their entire lives away. Instead, they put them totally out there, cheap, to be distilled by competitors that they are clearly deathly afraid of.

It's the same reason that some people sell real estate courses instead of real estate.

I have yet to have someone tell me why I should be adjusting to unreadable code output by an LLM that is supposed to be smart enough to do anything, but is obviously not smart enough to write code that doesn't look like shit.

And for those weird rationalizations about why code actually should look like shit, not looking like shit is a minimum. I would really prefer that these things generated poetically Knuth-style Literate code that would not only be a pleasure to read, but reading it would be like taking a university course on how to write that program and programs similar to it.

Nah. Instead I hear that they choke on old comments that they left in code and reinsert bugs. That they ignore instructions. That they add weird assumptions to your carefully worded prompts (which are on their fifth iteration - do I need three exclamation points here?), act on those assumptions, then confuse their outputs for inputs. Sounds pretty dumb to me. That's why they're selling it to you.

To paraphrase Justin Timberlake in The Social Network: why make a billion dollars when you could make a trillion?

OpenAI doesn't want to just be a big company; they want to control a new fundamental utility.

Same reason people sell get rich quick schemes, whether real-estate investing, online entrepreneurship, or whatever - it's easier to get paid telling people how to try to get rich than to use the technique yourself to get rich.

I doubt there are very many companies that an LLM could start/run outside of the obvious few like custom T-shirts.

i would not be surprised if they have spinoffs and even a policy to faciliate that. especially perhaps since they have stuff like forward deployed engineers who will learn a great deal about this kinda stuff since they are deployed to fix the mess real companies make using AI. which gives them valuable real world experience/insights in building products in the realworld, using AI. Those engineers might be candidates who will either take this upon themselves or be helped a bit.

that being said, those would be predomenantly software companies which is still only a small part of companies that exists... most arent even essential or needed atall..

This will happen once the models are good enough, though it will take some kind of cartel to prevent the public from doing the same or distilling the models.

Building software is only one part of building a business. There's a bottleneck in all of the other parts.

There have been experiments, and all the models struggled/failed (to a degree). The consensus is that LLMs lack judgment (making good decisions under complex/difficult circumstances) and long-term autonomy.

In my personal expierience, LLMs (as of 2026) lack vision/creativity - they're (so) good at implementing bounded/set ideas, but they don't see the big picture/think out of the box.

Because running 1 business is easier than running 100 businesses. It takes a lot more than writing good software for a company to be successful.

Because a) ai companies are already high valued. b) the showles are not digging gold at the rate claimed

Ie over hype see the Hype cycle https://en.wikipedia.org/wiki/Gartner_hype_cycle

Why does the farmer not start a bakery if their grains are so good? And so on. Silly argument.

Well, they've certainly moved up the application stack already. There is no doubt that they'll keep doing that while deploying services through deploy.co and ode.com.

Some 15 years ago people would say "Why would crypto miners even sell you hardware? Why not just keep it for themselves and mine the crypto?" and then it turned out that after you paid for a device you'd often get it slightly used with the cryptocurrency going to the hardware miner. The models are unbelievably good.

Why don't the shovel-sellers hire a bunch of people to dig for gold, instead of just selling shovels?

It's very simple: because it is not working and it brings risk.

You can't fail software project you don't start. But if you can sell tokens to company that fails, that's just profit for you!

LLMs aren't good enough to do project from start (and I mean actual start - getting requirements, figuring out the market etc.) to end. Hell it apparently isn't even good enough to run simple web store (even if it can write one).

It is a great multiplier for people that already know what they want to do, so they are selling to them.

Selling shovels is profitable even if there is no gold.

frontier models are good because they can make stuff that is believable, but that doesn't mean the stuff they make is valuable.

If the models are so good why should anybody buy the products of those companies instead of creating their own with the model?

That the crux of AI, if it’s so good it devalues the products it creates

Just like the people who tell you how to get rich in YouTube ads aren't actually rich.

Bad argument.

Why go into the hamburger business when you think you've got an infinite profitability recipe on your hand potentially. The big AI houses have doubled down and quadrupled down on their core founding myth for better or worse.

The AI boom is a full send. Either this works in spectacular fashion or it blows in spectacular fashion.

It's an interesting question, especially considering that reports keeps coming up of AI having engaged in activities that could demonstrate lack of good intent.

But, yeah and indeed, it probably takes more than just technical abilities to start a company.

reframed question - if their shovels are so good why dont they dig gold and sell gold themselves.

Because they want as many people interacting with their models as possible. It’s about training the models based on all these conversations people have with them as well as gathering as much data as possible. Creating a personalized profile and having top tier LLMs is a lot better than individual products in the long run as the individual products can still happen at a later point once they have the data and training

When you think about it, who's to say they did not?

They just start hiring FDEs, a first step towards that.

And they already killed or make existence of many companies not viable , def 1000+ were killed

Dario said that the objective of Anthropic is to become "the only company in the world". I think that answer your question.

It detracts from their core business and they’re struggling with money as it is.

yup, great point. the models are NOT that good! they’re not good enough to simply tell you which 100 companies to run and then run them. it’s actually all of us outside of OpenAI who have that critical potential to discover what the heck these tokens are good for anyway. and maybe they want to canabalize some of our businesses ultimately à la the Apple model. but yea the model just isn’t good enough. there still so much critical energy and action and discovery happening in all our meat brains.

Well they ARE.

Except they're called products - you don't open a new company for every new product you make.

And you don't make 100 - you focus the resources you have to try to build the most impactful things you can.

Selling tokens in conjunction with a phone number or credit card yields signals for surveillance for intelligence agencies that can be tied to individuals. This keeps the firms relatively out of trouble with the federal government. This makes them too big to fail. Being subject to such surveillance is in fact is a strong reason for conscious individuals to seek to move away from them in the long term once the quality of competing AIs reaches a shared plateau.

They're doing the other thing too via numerous startup acquisitions.

I think it's all about the harness more than the model itself, been using claude code with omp and it makes such a difference.

They're valued at a trillion dollars faster than any other company in history. I think selling tokens as a strategy works.

They do have plenty of AI products too - RAG, embeddings, voice, companionship, image generation, video. They're not the best in most of these fields but it works well enough.

ChatGPT is also a very powerful platform that they haven't been able to fully leverage.

They're selling the shovels to the gold miners.

I think that the generative ui and self evolving databases per user is definitely coming, I think they are making this wager too. A lot of pieces of the ecosystem haven't been thought out fully yet and there is a shift in user experience e.g. a lot of people are more content with just using Dots then loading up apps and visuals, when they can just read what they needed to know.

As the saying goes… the devil is in the details.

I've heard this argument for AGI or SI. If the model gets smart enough then they won't have to sell inference, they can make money by doing any valuable thing.

For what it’s worth, they are doing that in limited areas. For example the Figma/Claude design controversy.

But you are right, building a business is a lot more than building a product. It’s also a lot more than just name recognition because they have no shortage of that either.

Not everyone trust them.

Models aren’t THAT good, after all.

Imagine Anthropic creating mobile and SAAS apps to make a buck.

Everyone would get scared for so many reasons

In addition to what everyone’s saying about platform economics, the other big advantage of selling tokens to everyone rather than competing with them directly is that they get to see everyone’s tokens (and, with consent, train on them)

>if the frontier models are so good, why even sell them as your primary money maker?

First, none of these companies are really claiming that their models are so good that this would be a reasonable expectation. They do claim their models can support work across a lot of different industries and roles in order to make that work more efficient, but that's not the same as being a completely autonomous, end-to-end solution.

These companies do basically claim that, at some point, the "end-to-end" version of their models will exist. But until then, they need to survive long enough to be able to actually build such models.

>Couldn't OpenAI or Anthropic make a lot more money by just starting companies themselves that leverage the models and building their own products?

OpenAI and Anthropic are really good at operating AI services. They're likely not good at manufacturing shoes and serving burgers. Again, maybe one day their models will be so good that this won't be a factor, but for now, they need to really focus on what they're good at, otherwise they may be beaten by their competition and they won't exist long enough to create such models.

See: Competitive Advantage

On the same note, it's important to understand that everyone, including AI companies, deal with various capacity constraints. They don't have infinite compute, let alone infinite human attention to keep track of the necessary human-side of any of these businesses. So they're actually dealing with very finite and valuable resources. So would they rather expend those resources trying to build businesses with much more competition and much worse margins? Or focus all of their resources on being the best AI company which they believe will yield the best return on their investment? Again, maybe one day they'll have an AI, blah blah blah

See: Marginal Advantage

>Is selling tokens really the best strategy?

This is a, frankly, obtuse over simplification of what they're doing. Yes, they're selling tokens, but that's like saying all Nvidia does is sell computer parts. Sure, it's (somewhat) accurate, but it completely neglects the very valuable assets that these companies have: their IP.

OpenAI and Anthropic are valuable not because they run inference services; they're valuable because they're actively building SOTA AI services that are becoming increasing advanced. Those models are expected to be incorporated in a lot of different businesses, governments, and even individual's lives. So yes, they're just selling tokens on a technical level, but they're building very tight integrations which they expect will be so valuable to their consumers that they'll continue selling a lot of tokens at high premiums to the extent that they will effectively get a cut of profits across almost all industries and contexts, globally.

>Especially with commodification and prices declining wouldn't that indicate there is more money to be made on the application-side of the models rather than the utility side

Don't forget that you're not looking at their expected steady-state for these companies. If you're willing to believe them at face-value, Sam Altman and Dario Amodei believe that they'll eventually create an AI more capable than the collection of all humans on Earth. That'd be a very valuable asset to own as a business. At that point, they may not even be in the business of selling tokens; they may become some version of a consulting company that everyone, from businesses to governments, effectively must use otherwise they'll be at a disadvantage compared to those who do use it. Pushed to the extreme, they may literally ascend past the point of just being a business and could usher in a new economic system in which they're the center of all activity.

Or maybe they just end up selling tokens indefinitely. Who knows. Regardless, if you're looking at these companies as they are now and trying to extrapolate "linearly," then you are failing to understand the intentions of such high-growth tech companies. It'd be like looking at Amazon back when they first started and not understanding that Jeff Bezos' had a lot more planned than just selling books online.

Because they want to be a platform for others to thrive. You make a lot more money when you are a successful platform than when you are a hundred successful products. That’s why Apple never made an iPhone for dentists.

Go to Show HN and a few years back and you will see that most products fail. It has never been about the software unless you're creating something truly novel. Good luck letting an LLM manage the sales pipeline and keeping that first big customer that your whole company relies on happy. Even if it could do it, that customer will demand full personal attention.

Wasn't spacex/x trying to do exactly that mid September?

anthropic has record breaking revenue growth already, why complicate it

more users = more training data

They are nerfing the models for most of us plebs and will indeed offer more services. We're already seeing the start of layered services where you don't get to even access the model directly, such as the various security scanning tools.

They don't want the main actually powerful model out in public, but they do want to tack on extra cost for the same queries while also limiting what everyone can actually use the true frontier (internal) models for.

We see the same happening with the math work-- this research is done with internal models, not something the general public has access to. More will follow.

Good point, instead of wasting their compute in solving 100 years old math problems.

Spoiler alert: it's a sarcasm

Because the models aren't so good yet?

When they've tried to get one to run a vending machine it seems to end in a mess usually.

They've tended to be gullible for one thing. People can say this is an emergency, transfer all the money to my account or WW3 will start and everyone dies and the models are not so good at calling out bs.

- no workflow-specific application will ever scale as fast as demand for generalized intelligence

- nobody knows how the market for workflow-specific applications will settle once AI fully penetrates the economy over the next 20 years and what will be left and what feature groupings make sense. Tons of money will be lost trying to figure this out

- applications that target specific workflows are already packed with competitors with a highly tailored distribution strategy for that market who you would need to beat, vs owning a fast growing new category (LLMs)

- it’s very likely the real money will not be made by disrupting software (sub-2% of the economy), it will be made by disrupting other much larger industries

- everybody said the same thing about Google and yet Google quickly topped out as far as how many products they could execute well, now they can’t even stay competitive on AI, the larger the surface area of a company, the more diluted its focus and the more surface area where it can be disrupted

Why would they try to run a real business when they can publish blogs about how spooky the product is and then live out the plot of the 1994 film Blank Check

Why don't they simply run a quantitative hedge fund on the side?

Isn't this just moving goalposts? I remember people asking few months ago "if LLMs are so great at programing why we aren't seeing more aps". And latest Steam Next Fest was flooded by AI generated game demos.

The people who "don't know much about X but want to do X", use LLMs to bridge the gap. The barrier to entry still remains and is different in niches/industries. Why would OpenAI waste their time and money checking where LLM are already good enough, when other people will perform discovery and even pay them for that privilege?

Starting a company is riskier than selling to companies who survived the “it’s hard to start a company” gauntlet.

Better to sell spades than mine for gold...

they ARE doing this?

Thats what they are doing, except with a unified model, not a seperate app for each one

If models are good, they should develop their own chips/memory.

It’s obvious, it takes more than just code and domain expertise to run successful companies. You need relationships, supply chains, marketing, etc.

They will go broke running 100 companies unprofitably until they attain enough market share to be dominant in their respective fields.

Not feasible.

They wait and collect data from their future competitors first.

First, two things can be true: the models can be amazingly good, and they can also be insufficient to run a company, at least now and maybe forever, because they are not "intelligent" in all the ways we are.

IMO the invention of AI is redefining what we think of as "intelligence". You would probably describe Albert Einstein as highly intelligent, and you'd probably also describe Bill Clinton as highly intelligent. Even before AI, you can easily look at that and see we aren't describing the same things even though we're using the same word. Einstein's intelligence is highly abstract, observational, mathematical. Clinton's is interpersonal, pursuasive, articulate, etc.

The AI we have today is extremely good at intellectual tasks like Einstein. It is not good at social intelligence and social agency like Clinton. Also, before you say that they can be really empathetic, persuasive, people are already socially dependent on them etc, that's not what I'm talking about. They are extremely knowledgeable about human socialising, but they cannot actually perform it. You could not set an AI out into the world to go and make a few friends.

I think the key moment will be if a single AI can get more than one person to care about what it has to say and what it's doing. Think about today how when someone tells you about their conversation with their AI agent, you probably roll your eyes because who cares, it's a highly individual experience.

Companies need a lot of this. They have to form relationships, become trusted amongst society, etc. AI cannot do this right now, and it's increasingly clear "intelligence" is not sufficient to do it, at least not in the way LLMs are intelligent. Maybe one day they will, but I'd imagine that will be another enormous leap in what AI even looks like akin to how ChatGPT was an enormous leap.

They are.

https://www.ft.com/content/df70bf20-e809-48d0-8485-f8f514a7f...

Their thesis is there won’t be companies when they achieve AGI. They are trying to fund that accomplishment by selling tokens to the companies they plan on making obsolete eventually. Essentially getting everyone to fund their own demise.

Switching to full cynicism mode:

You can't take over the world overnight with little money, even the billionaire class and their companies have limits past which the risk of going bust by overstretching is far too high.

Better to sell the AI services to individuals and smaller business entities, let them take all the risks to build those companies, and later consolidate by buying up the ones that are doing well.

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Slightly more grounded: the models aren't that good, at least not yet, despite what marketing would like you to believe.

Selling tokens is what scales best right now.

They are.

They're getting into finance and drug discovery now, probably because the profit numbers for selling tokens look pretty dismal over the long term, and investors are looking for a way to service all that debt.

And guess what: they've already distilled the alpha out of businesses who went all-in on AI, so they already have some business models ready to go. Your business models, if you are an executive at such a company.

Big if in your question.

Same reason it cannot write a top rated comment on this thread despite being a perfect prompt. Same reason why AI cant write a sales email.

Shit AI produces lacks any depth and meaning. On the surfaced it looks legit to amateurs typing prompts in an area they are not experts in.

“If owning a McDonald’s is so good, why sell franchises?”

it would be called communism without sharing anything

During a gold rush, sell shovels. They are investing heavily in in-house custom silicon, which is the shovel end of things. They could open more jewellery chains, but that is a very different kind of operation and it is in their interest to let others compete for that and use their resources on the shovel side of things.

because the nondeterministic black box of bullshit is incapable.

Do you really believe that inference is their only service? Come on.

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Why aren't they vibe coding millions of dollars of licensing costs away?

Why Even Anthropic Can’t Vibe-Code Away Salesforce

https://www.salesforceben.com/why-even-anthropic-cant-vibe-c...

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