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.

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.

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 .

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.

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

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.

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.

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.

Why doesn't NVIDIA just make the best frontier model?

Why doesn't TSMC just make the best chip design?

Why doesn't ASML just make a fab?

The real answer here is that OpenAI and Anthropic are in the middle of an intense race, and the payoff of having the best model (or one of the two best) is so large that it makes no sense to focus downstream.

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.

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.

https://apnews.com/article/ai-artificial-intelligence-sweden...

San Francisco-based startup Andon Labs has put an artificial intelligence agent nicknamed “Mona” in charge at the eponymous Andon Café in the Swedish capital. While human baristas still brew the coffee and serve the orders, the AI agent — powered by Google’s Gemini — oversees almost every other aspect of the business, from hiring staff to managing inventory.

https://futurism.com/artificial-intelligence/google-gemini-r...

Some of its questionable business decisions include ordering thousands of rubber gloves, despite the café only having a handful of employees. The AI’s handlers, nonetheless, are holding out hope that this is just a blip from expensive setup costs. How well it performs will raise grander questions of the tech’s impact on the workforce.

“AI will be a big part of society in the future, and therefore we want to make this experiment [to] see what ethical questions arise when we have AI that employs other people and runs a business,” Hanna Petersson, a member of Andon Labs’ technical staff, told the AP.

To launch the experiment, Mona was given a simple set of instructions. It should run a profitable café, be friendly and easygoing, and try figure out operational details by itself, Petersson said.

---

And that last part is the "why doesn't a LLM company open up a company to sell its wares". There is knowledge from life experience that a LLM doesn't have.

For a product, you need to recognize a need in the economy... something that irks you that you can make better. Go through https://www.npr.org/series/126166186/from-scratch or https://www.fromscratchradio.org/show/ (or any other podcast service) and consider how often those companies were founded on something that was recognized as a need or something missing that comes from the human experience ( https://www.fromscratchradio.org/show/mick-mountz for Kiva systems ).

---

The company represents risk. The coffee shop needed money to start... and it failed. https://kotaku.com/google-ai-put-in-charge-of-swedish-cafe-b...

Creating companies making applications that people don't need is wasted money.

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.

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)

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.

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

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.

Secondly even they are constrained by resources. They have a limited amount of people/GPUs/capital. Given the constraints its best to focus your attention on the highest ROI given your team and organization.

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.

- 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

But ultimately because if they did, everyone would flip the f*** out. It's the same reason that Google doesn't openly do it. They have former VPs of Google found new companies, or invest in new companies, that all use Google Cloud and have all juicy corporate secrets flow through Google Mail without end to end encryption but are like totally not front companies for Google.

In the mid 2010s Google was way too aggressive with trying to get data from healthcare organizations and they got told to piss off. So they made front companies where the data will flow through.

At the very top there's a bunch of dudes running around in the woods naked and something is lit on fire at the end of the festival. Like Burning Man but without the stupid hippies.

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.

Also why are they any better positioned to open a company than anyone else. Everyone in the world has access to tokens at a fairly low cost. They don’t have any unique advantage as the token creator.

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

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.

Why would OpenAI start a hundred companies when there's plenty of prospective founders to take that risk on their behalf?

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

At some point we will be wearing mocap suits and remote controlling bots to create training data, it will be sold as doing any job remotely :^)

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.

[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.

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)."

Management Consultants are usually accountants, not technology people who too often analyzing and providing a report and strategy and as much as possible except implementation let alone delivering the outcome. Junior labor is more profitable than senior labor. It's easier to hire someone for advisory, then consultants, who then get contractors to bang it out and by then who knows what got lost in translation. For a good while, I worked in rescuing these types of projects.

The model providers are often rooted from being researchers so they also have likely not spent much time in industry, let alone so many different industries. This is why we can see posts by leading AI folks who are sincerely amazed by how models are being used in industry.

That B2B experience + operations is on a different level because it exists in people's heads and not in the models.

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

Can AGI figure that out. Maybe, but I think it is very likely that AGI will also have to fail in the real world, and then develop those learnings that those companies have done. There is no way to circumvent this computation, you need to do these steps to even know what the correct solution is. I like to think of it as playing chess. Intuition helps in directing exploration, but any agent, human or machine has to explore down a minimum number of paths before converging to the optimal move. There is no algorithm that can generate an optimal move without this search, P!=NP says something similar, exponential search can’t be done in polynomial speed.

Stephen wolfram says something similar, superintelligence, whatever cannot predict the output of the trillionth step of a cellular automate without calculating all the steps before it, there is a minimum amount of computation required, the problem is computationally irreducible below that.

So maybe in the future, with humanoid robots, AGI can decide to start creating a Walmart competitor. Then it will make a large number of mistakes and it needs to learn from, this could mean continual learning or maybe just memory in markdown files if that’s enough. It needs to hit all those failures quickly till it finally has something as efficient and capable as Walmart. And this is to just become a capable competitor, during this time you will keep burning money and to surpass Walmart, you have to do far better which is hard, how much more efficient can Walmart be, idk.

All to say, OAI starting its own company is a losing proposition, huge capital, unclear benefits, high risk. If OAI just provides AI to Walmart, they can make money immediately and Walmart can become more efficient by firing its human workers, which is the problem we are stumbling into.

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.

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.

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.

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.

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.

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.

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.

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

There are some money managers that don’t take in external money (I think TwoSigma started that way). Which could mean there might be someone out there that just does crazy good apps with their own model and don’t sell the model in form of tokens. We can’t know that by definition but the maths of tokens suggests that’d be very unlikely to exist at least right now.

Secondly, I think they are doing that. All the functions that their harnesses take on are businesses they are taking money from. It’s just not in the form of SaaS as we know it.

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.

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.

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.

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.

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.

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.

1) Provide resources that are relatively cheap for them to any startup that registers. 2) Look for early signs of success. 3) Pour actual investment on the winners.

Most AI use cases involve the Internet. So let's pretend that OpenAI agreed w/your logic and did this. They'd have tons of businesses on the Internet, whose lifeblood is Internet traffic... and on the other side of this, controlling the spigot of all this Internet traffic, is Google.

All Google would have to do is to wake up one day and say "we've decided to depriortize low-quality AI businesses to protect the consumer" and they'd be dead.

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.

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

there's a year old rumor around San Francisco that frontier lab employees are so expensive to poach because they trade options with unreleased models and infrastructure

it wasn't about the value derived to the company justifying these large packages. it is now. but there is also that other competing force.

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.

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.

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.

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.

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.

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.

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

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

But yes, they are! That's what DeployCo is for!

1. Consult companies

2. Buy the highest leverage ones

3. Operate them

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

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.

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

Not feasible.

The main consumerisation of their products are Dots or Duet. Which are similar to Meta Muse or Grokbot.

On the Enterprise-side Anthropic has partnered with Salesforce with Claudeforce.

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..

Yes you can get make it big using LLMs, but it's still high risk, like starting any new company. It's lower risk to just sell the tools.

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

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

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

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

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.

Kind of like Amazon.

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.

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

Many don't want to say it or admit it.

Spoiler alert: it's a sarcasm

You could ask the same question about any supplier. If your CPUs are so good, why not assemble PCs? If your lumber is so good, why not build houses? If your vaccine is so good, why not start a chain of pharmacies? Empirically there seems to be benefits of specialization and focus that outweigh the benefits of conglomeration.

Knowing what customers want is crucial, and people who buy our tokens often understand their customers better than we could hope to. The are also opportunity costs. For every bit of effort we expend chasing a new vertical, that’s a bit of effort and focus subtracted from our core competency.

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.

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.

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.

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.

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.

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?

more users = more training data

But I like the implied hype-conspiracy that models aren't so good. Let's see post-IPO!

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.

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.

Even then we have lots of projects that claim to deliver incremental net profit. Why not just do them all?

The obvious answer is limited resources and risk. Those numbers are never real, and there are lots of costs you don’t think of.

Less obviously is gross margin %. If you begin to dilute your high margins just to make extra cash, your % dilutes and this is a bad thing. Your money should be working toward the most profitable thing per dollar invested.

Also, focus. If OpenAI has to focus on two rabbits, they won’t catch either (or 100 rabbits in this case). They have 1 thing they should be focused on, and all bets should lead to that road.

One exception is that you also need to invest in projects that aren’t profitable, like safety and regulation, etc. But I could still build a business case of how much profit we’d lose if a bunch of consumers got sick or hurt off x if I want to complete the exercise.

Why not just hack into the military, take over the strategic command and conquer everyone?

Using AI to generate companies to make fiat to buy stuff means you're not ambitious enough.

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.

Everyone would get scared for so many reasons

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.

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