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.

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.

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".

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.

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.

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.

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.

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.

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

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.

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

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.

Since the AI models are better at thinking fast and making decisions, OpenAI should just let their AI buy and sell stocks on a stock exchange, and it should double or quadruple any amount of money that they give it at the beginning, only in a few days.

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

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.

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.

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.

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

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.

Not everyone trust them.

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

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)

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.

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.

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.

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.

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

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.

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

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?

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.

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

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'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.

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.

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.

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)

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

Spoiler alert: it's a sarcasm

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.

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

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...

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.

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

They wait and collect data from their future competitors first.

Big if in your question.

Selling tokens is what scales best right now.

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

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.

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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