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...
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.
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 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)
Wasn't spacex/x trying to do exactly that mid September?
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)
Just like the people who tell you how to get rich in YouTube ads aren't actually rich.
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.
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.
Big if in your question.
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'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.
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.
Thats what they are doing, except with a unified model, not a seperate app for each one
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.
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.
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.
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 wait and collect data from their future competitors first.
Better to sell spades than mine for gold...
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.
Do you really believe that inference is their only service? Come on.
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.
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.
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
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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.
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.
because the nondeterministic black box of bullshit is incapable.
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Good point, instead of wasting their compute in solving 100 years old math problems.
Spoiler alert: it's a sarcasm
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If models are good, they should develop their own chips/memory.
Selling tokens is what scales best right now.
Starting a company is riskier than selling to companies who survived the “it’s hard to start a company” gauntlet.
“If owning a McDonald’s is so good, why sell franchises?”
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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.
Forward Deployed Entrepreneurs.-
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".
It is this, but for a globalised shovel seller selling shovels to the entire world population, for people all over the planet to start digging in random places in the hope of finding gold. Very wasteful and not likely to end well for most people, but likely to make a very small number of shovel sellers much richer than if they'd just used their own shovels in areas with known gold deposits.
Being one of the premiere AI companies is much more exciting to investors than "running a company using AI" which everyone can do
I agree, OpenAI is one of the leaders of the industry and the vision they have sold to investors of the great advancement of the human race is why they are valued at 852bn. Though most outlets and statistics say they are not making a profit, it's also just more axiomatic that OpenAI would focus on their firm's core business which is AI. Building another 100 companies is futile for them, though a little diversification can be advantageous.
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.
1% * 100 is... 100%
(and diversified risk)
a better reason might be that people would not want to use OpenAI because they might be sherlocked.
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.
Giving strong "if my grandmother had wheels she would have been a bike" vibes and I don't know why.
Why don't they simply run a quantitative hedge fund on the side?
Leopold Aschenbrenner tried this and got eaten by the wolves as far as I can tell...
I mean it sounds stupid but I think its a fair question if you can spend 15 million and solve a millennium prize problem, what happens if you take the same resources and just aim the cannon at making money?
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.
who will be in the bread line if it blows
The standard analogy is selling shovels, not hamburgers.
OpenAI is selling people access to a tool to build things. OP is asking why they don’t just build the things themselves, which I believe is a fair question.
The bet here is that it's not selling shovels but rather magic.
...a dubious proposition except this time there is a small but real chance it may be actual magic
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.
really great analogy, it’s like selling shovels in a gold rush type of thing
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?
not really, many people could confidently predict 2 years ago that AI was going to be great at coding
I don't see any evidence that it can build a business
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.
You can just restate the question then to say: If the models are so good, why can't they run a business?
What does "so good" mean? AI models are very good at doing [a set of things]. Autonomously running a large, complex business is not one of them.
This is just a form of "if you're so smart, why aren't you rich?", isn't it?
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.
The models are also insanely inefficient and economically unviable to actually train and run. They’re doing the Uber style model of hoping they can keep afloat long enough to make other businesses go bust and then they can snap up their customers/market and amp up the prices
I doubt if we will ever get AGI.
I talk to a few models, they talk to each other. Together we’re AGI. Hybrid, but still.
Ten years ago people would have unambiguously identified what we had today as AGI.
Unambiguously?
As long as you don't see thousands of AI businesses that are run entirely without humans people will reject the idea that they are AGI. People could easily do that today if these models were AGI since its not hard to put them in a loop and tell them to run a business, so we know when that threshold is reached.
And if the AI isn't general enough to handle every part of a business well then you will not convince people that its AGI.
This hasn't changed from 10 years ago, this level was always what people imagined about the future of AI.
Ever is such a strong word.
Doesn't have to be for literal ever, just not until we (humans) blow ourselves up - if we don't achieve AGI until then, that's effectively ever. And you could gamble we'll blow ourselves up or make the planet uninhabitable before AGI.
And AGI is such an undefined word.
Building software is only one part of building a business. There's a bottleneck in all of the other parts.
But LLMs can do that now? Surely you could only have one or a few people managing everything with them. Or just have them build code that fully automates also that. After all software should be solved issue. So no point of not automating software for all aspects needed and then letting LLMs handle the rest.
Software might be solved, but not everything is solvable by software.
1. Anything that can be easily done with an LLM can be done by anyone easily. Given that, the value of those things therefore drops to near zero.
2. All remaining things are at least as hard to do as before, but you may have removed some load from people that previously were more busy doing things from the (1) category manually. So these might drop in value a bit as there are more hours available with the existing people to do those.
3. Then, there are things that become harder because somebody used an LLM to do them. Imagine you have a project lead who didn't do one bit themselves, generated a bunch of specs and tickets using AI and handed them to you. You are the first one looking at them manually and you find out that they are garbage. Now, in all likelihood you have lost efficiency. This in my experience applies to all types of work that yield results which are hard to verify.
Which of those cancels out the other and what kind of feedback effect arises and what overall effect on productivity/efficiency this has, nobody knows.
reframed question - if their shovels are so good why dont they dig gold and sell gold themselves.
Gold is much more fungible than a business. 100 different businesses are much more unique than 100 different gold nuggets.
The counter-argument is that the models might make business ideas just as fungible as anything else.
I thought NVidia was the one selling shovels here, not OpenAI.
This fits, if NVidia fully believed in the LLMs/AGI future, why would they waste their super valuable GPUs by selling them? Why not just make your own LLM with the advantage of being one of the few major compute providers?
Nvidia already does that, their models just aren't competitive.
Google is doing it successfully to the point where they only let you rent their shovels and never let you buy them.
There's some kind of skill needed in an organization to make those llms. Openai and anthropic were able too. The other llm creators, not really. There's no guarantee that Nvidia would be another leader and not end up like meta or xai's attempt
Deepseek claims to be making $38/gpu/hr on deepseek 4.1 flash, and I would say that’s probably marginally close to the frontier, so they don’t have to be as good as OpenAI/Anthropic. Even at half that revenue, NVidia makes back the cost of a b200 cluster in roughly half a year. (19*8*24*5*52 = 948,480)
It’s estimated NVidia sold 4.5-5.2 million gpus in 2025 with total revenue numbers at about $130b.
With this terrible math in mind, they could produce half of that and make substantially more money, basically an infinite money glitch.
Yeah, but I also don't think it's that deep. E.g., by the same line of thinking, TSMC should be doing what Nvidia / Apple / AMD are doing, and ASML what TSMC is doing.
NVidia is good at making the shovels, and sticks to that.
It’s not, but for fun I think that depends on if you see the models as just another technology or as a “country of geniuses in a datacenter”. The former means NVidia believes LLMs are fundamentally limited, and if that’s the case OpenAi and Anthropic are basically screwed as their core products become commodities.
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.
Even after the singularity the almighty AI has to work to pay rent...
Imagine the Earth is covered in a "Grey Goo" outbreak of spreading nanotechnology, infiltrating every corner of the planet in a constant churn of molecular and informational warfare. Eventually it leads to vast colonies of nanobots which rise thousands of units high clambering across the land, driven by vast inscrutable colony-minds.
I can tell you with 100% certainty that they will pay rent, because they are us.
Does the grey goo need solar panels, or does it contains the requisite genes ?
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.
> including the ops
Citation needed.
> 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.
They don't have to do it openly.
Indeed, they are doing this, just slowly and strategically, to not turn off the knowledge tap. A major company I do some consulting for just migrated from Figma... to Anthropic Claude.
How long until people switch from iOS or MacOS to ClaudeOS?
The downfall of Apple may be closer than people think.
how do i bet against that?
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.
I thought the agents were largely autonomous, and should replace workers?
If labor is not your constraint, you wouldn't be diverting your specialization.
I believe this is the correct answer. You can't run 100 businesses because each one would only receive 1/100 of your attention, and they would all perform poorly.
But that’s the gist of the question, can’t their internal frontier models provide that infinite attention? That is what their PR implies.
I think that’s a different argument. Apple absolutely “copies” hugely successful, durable apps. Just read about “getting sherlocked”. The rest of the apps are transient, niche and it’s easier to just harvest your cut of ads/payments.
Fair point about Sherlocking, but that's actually proves the analogy. Apple only "Sherlocks" broad, consumer-facing features, but they never touch specialised B2B or super niche software. AI model providers are doing the same thing. They build the broad stuff themselves, like AI inside Excel or PowerPoint, but they live the crazy stuff to other companies.
I wonder what is stopping apple from cloning the top ten apps in each category using AI and then booting the original developers off the app store.
Good morals.
idk they’ve created the most used and differentiating apps though
They aren't in the top 10 for either free or paid apps.
https://apps.apple.com/us/iphone/charts/36
That actually makes me wonder if Apple apps are not included because they come pre-installed.
i am referring to imessage, camera, photos, facetime, and so on
> No single company can be specialised in everything
Not everything, but a company can be specialized in a lot of different things, Samsung for example, or megacorp in Japan.
Yeah, actually trying to specialize in everything constraints the firm's growth. Though diversifying can always bring some much-needed revenue like you said with Samsung or Tata in India.
Or amazon that can undercut any merchant on their platform by cross financing the losses by selling more aws servers.
That’s the other side of diversification: undercutting your competition until they go out of business. Then prices are raised again.
Yeah Amazon is another example I mean they do a lot of things too. AWS has changed software and Amazon prime which is a vehement competitor to Netflix and disney+ market share.
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.
3 is biggest point imo.
Openai haven't yet amortised their current investments into the space and nor have they stopped making new ones.
I'm sure they'd be totally capable of bringing 1k new biz online but that's even more debt, and even more uncertainty.
Some variation(s) of 5 is carrying a lot of weight. Need a person with an Idea. Need someone to refine their idea. Need someone to spend the time filtering through the slop to find the good bits. Much better to sell people on the idea of their dream being created while you sell them tokens to do that.
That all said, A person trusting the big AI companies with their golden goose idea seed leaves a lot of concerning openings down the road if that idea gets "leaked" out to others. Similar concern of mine with if the LLM outputs that made your idea happen to be reused by the big company if someone else asks similar enough questions or otherwise coaxes the AI to reveal what it did for you.
All this AI generation is gonna be a lead to a wild time for IP law.
Is 4 correct or incorrect? What data do we have so far in this regard?
AI price-performance is improving rapidly. AI usage, whether in tokens used, in cash spent, or any of the above performance-adjusted, is curving upwards too.
Causality is uncertain, but the "Jevons paradox" interpretation is certainly not contradicted by the available data. Anecdotes of per-employee AI spend rising, and multi-agent freerunning AI tasks becoming more common are also plentiful.
Personally, I think that the "Jevons paradox" interpretation is basically correct. Humanity doesn't have a limited demand on intelligence - but humans are expensive, so it's supply-constrained. The cheaper intelligence gets, the more of it ends up used. As AI gets cheaper and more capable of substituting for human intelligence, usage will rise.
>3. They need revenue yesterday. Increases in borrowing rates means access to capital isn't what it was in the 10s
This is a huge problem, why is it like this
The 10s were totally fake due to ZIRP.
> why is it like this
In part it is like this because they've already borrowed so much.
They have borrowed almost nothing.
Investment isn't debt.
Exorbitant Cloud costs and spending 22 million to solve a 1 million dollar maths problem isn’t investment though.
Investment isn’t debt, but investment and debt demand revenue in functionally identical ways, and OpenAI has taken an enormous amount of investment, so they are subject to broadly the same pressures as a hypothetical company that had borrowed lots, no?
Isn't investment like a form of debt, or well obligation to make returns?
If VC provide you funds, there is an expectation of returns, otherwise the board would vote you out.
Yeah it's not a traditional loan from a bank, but it's not a 0% interest loan either.
The duopoly AI labs haven't technically borrowed much, but a metric ass-ton of money has been borrowed by various other entities in service of them as infrastructure proxies.
That's what is driving up the cost of debt and teetering some of these companies into junk status.
you can say coreweave
they've borrowed so much they're directly competing with national governments in capital markets.
That’s mostly not the Frontier Labs. They’re definitely creating a lot of the demand but the people taking out those loans are Neoclouds and Big Tech (hence why Facebook + Google et al suddenly all have terrible cash flows after years of having more money than can be spent).
AnthropenAI are the ones driving a lot of that infrastructure spending when they’re such big consumers of compute but they’re not the ones feeling the brunt of the infra spending. Although those costs will bubble up to them indirectly eventually.
OpenAI has hardly borrowed anything. They have a $4B revolving credit line but have hardly touched it. They haven't issued any bonds.
Investment isn't debt.
The rates environment directly dictates what capital is available to OpenAI and at what terms. When potential investors can get x% virtually guaranteed, then they are less willing to give cash for equity to OpenAI.
They owe people hundreds of billions, possibly even over a trillion. They've just been very clever in how they've structured it, so on paper they have low debt.
I think there’s some crossed wires here with the wider data centre build outs. OpenAI have their own flavours of sketchy behaviour but I’m not aware of them solely being on the hook for those amounts short of some weird accounting of Microsoft cloud costs onto them or something.
> Investment isn't debt.
...yet.
SoftBank is very leveraged with …… debt.
One of the biggest AI investors.
With investors like Softbank, who needs competition?