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epsteingpt 22 minutes ago [-]
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.
moezd 13 minutes ago [-]
Exactly. Factories will be built, but you will still need workers, project engineers, and actual architects. Automation is still not there yet, despite the elaborate harnesses of frontier models.
sevenzero 4 minutes ago [-]
Given the primary goal and promise of all these AI vendors is to replace workers I think its hilarious that "you still need workers" is an argument. Wouldn't we have an abundance of workers soonish as all the replaced people could be retrained? Or is the truth that these models can't actually replace intellectual work?
alexsaintx 8 minutes ago [-]
Best response I've ever seen to this. Well said.
api 20 minutes ago [-]
I think this is true. I also suspect there’s aspects of human intelligence not yet replicated, but it’s not clear what those are yet.
maxdo 23 minutes ago [-]
The question is answered 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 .
jonnat 2 hours ago [-]
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.
oblio 1 hours ago [-]
Put simply: who not build the perpetual money making machine if you can?
chandureddyvari 9 minutes ago [-]
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
CoolestBeans 15 hours ago [-]
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.
fennecbutt 13 hours ago [-]
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.
discordance 3 hours ago [-]
To make point 3 happen fast, their army of Forward Deployed Engineers roam inside existing companies and build for the companies using the companies subscriptions.
le-mark 1 hours ago [-]
Is this a thing? Where can we learn more?
fn-mote 1 hours ago [-]
I believe the point is that every software engineer using AI is one of those “Forward Deployed Engineers”.
Although the point would be equally valid if they were OpenAI consultants. (Imagine paying twice for the help: once for the consultant and once for the tokens.)
physicsguy 48 minutes ago [-]
On 1) though, they're an inch deep and a mile wide.
lconnell962 5 hours ago [-]
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.
le-mark 1 hours ago [-]
This framing is a bit off; or from an entrepreneurial perspective which isn’t applicable to the automation of the overall economy. How economists model automation is task replacement. Work consists of tasks some core some ancillary. Ai is clearly more suited to text and command line tools making coding an ideal task for ai. Other text oriented tasks follow; math, law, etc. implementing systems to move tasks toward ai and eventually robots will take time. Similar to how it took time to build out roads and gas stations and cars to utilize oil and gasoline.
harvey9 47 minutes ago [-]
I think it was from an entrepreneur perspective on purpose. Can something almost entirely built on AI compete with a human business? AI isn't going to do car repairs but it might handle the things you listed.
redanddead 15 hours ago [-]
>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
rsalus 14 hours ago [-]
they've borrowed so much they're directly competing with national governments in capital markets.
nl 14 hours ago [-]
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.
MisterMunchkin 4 hours ago [-]
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.
nl 15 minutes ago [-]
"On paper low debt" actually means.... low debt.
Tanjreeve 3 hours ago [-]
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.
estearum 3 hours ago [-]
Don’t they have a fully committed preorder for like $500 billion in compute from Oracle starting in 2028? And Oracle is funding that buildout with junk debt?
chiph 1 hours ago [-]
Oracle is the one with the debt. OpenAI has an order/contract (promise) to someone else.
Presumably there are penalties if OpenAI were to cancel that order (I am confident that Oracle's army of lawyers made sure to include that). That's the unmovable rock on OpenAI's books, not the data center.
fn-mote 1 hours ago [-]
> junk debt
Not a useful term, here.
AIUI, the building is funded by making the people who order it part owners in the new data center company. Not sure and I don’t care enough to find out; clarification welcome.
CoolestBeans 11 hours ago [-]
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.
bigyabai 14 hours ago [-]
> Investment isn't debt.
...yet.
nojvek 12 hours ago [-]
SoftBank is very leveraged with …… debt.
One of the biggest AI investors.
bigyabai 10 hours ago [-]
With investors like Softbank, who needs competition?
Tanjreeve 3 hours ago [-]
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.
aenis 2 hours ago [-]
Indirectly? They have contracted the capacity with the likes of Oracle, this is not 'debt' in accounting sense, but it is a financial commitment that will require either taking on debt, or getting more investors.
15 hours ago [-]
rayiner 14 hours ago [-]
The 10s were totally fake due to ZIRP.
georgemcbay 15 hours ago [-]
> why is it like this
In part it is like this because they've already borrowed so much.
nl 14 hours ago [-]
They have borrowed almost nothing.
Investment isn't debt.
fwlr 6 hours ago [-]
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?
nl 18 minutes ago [-]
> investment and debt demand revenue in functionally identical ways
No they don't.
A company has legal obligation to pay loans at the agreed rates.
There is legal obligation that defines rates of return beyond "acting in shareholder interest" (and OpenAI is a public benefit corporation so even this is reduced).
alt227 3 hours ago [-]
So all those hundreds of billions of dollars investors ploughed into OpenAI was just a gift was it? No expectation of a return of any kind? What if that investment money was originally borrowed by the investors?
nl 16 minutes ago [-]
If the money was borrowed it would have to be paid at an agreed rate.
Because it's an investment it is risk capital. They won't be happy if they don't get a return but their return is part ownership in the company, not a legal contract giving an income stream.
georgemcbay 14 hours ago [-]
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.
redanddead 7 hours ago [-]
you can say coreweave
timothyduong 14 hours ago [-]
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.
nl 35 minutes ago [-]
> Isn't investment like a form of debt, or well obligation to make returns?
No.
> If VC provide you funds, there is an expectation of returns, otherwise the board would vote you out.
A person might get replaced as CEO but the company has no financial obligation to the investors.
A loan means the company does.
Legally they are dramatically different.
Tanjreeve 3 hours ago [-]
Exorbitant Cloud costs and spending 22 million to solve a 1 million dollar maths problem isn’t investment though.
fn-mote 1 hours ago [-]
Fake costs. The numbers reported are what they would have charged other companies for the tokens.
JacobAsmuth 15 hours ago [-]
Is 4 correct or incorrect? What data do we have so far in this regard?
ACCount39 4 hours ago [-]
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.
adelekeabdulgan 44 minutes ago [-]
"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.
vanschelven 26 minutes ago [-]
but even in a gold rush selling shovels _at a loss_ would not seem to be the best strategy, unless there would be some kind of shovel lock in effect.
blitzar 35 minutes ago [-]
the real shovels are gpus
trzeci 32 minutes ago [-]
the real shovels for the real shovels is energy
mattbrewsbytes 19 minutes ago [-]
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.
Lerc 31 minutes ago [-]
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.
echelon 25 minutes ago [-]
In a few years, they'll be able to do this. It's still too early.
wolttam 18 minutes ago [-]
It just won’t be a chat box. You need something that is always there and listening (at least during work hours), asking questions and figuring out the entire scope of the business, before they will be able to come up with (useful) ideas.
stemonteduro 2 hours ago [-]
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
mochidusk 14 hours ago [-]
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.
chris_money202 1 hours ago [-]
I don’t think I agree with a snack company having an easier time becoming a packaging company. Sure they know what they need but outside the idea there’s almost no overlap in the companies business units
Neither would be easy for either to do
harrouet 6 hours ago [-]
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.
dwroberts 3 hours ago [-]
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
phoghed 18 minutes ago [-]
> economically unviable to… run
Didn’t DeepSeek just disabuse us of that notion?
> …with overall revenue of US$38 per GPU-hour (at valley pricing)
I asked my AI girlfriend whether AGI was inevitable and she said my question was brilliant and insightful.
lukasm 4 hours ago [-]
I talk to a few models, they talk to each other. Together we’re AGI. Hybrid, but still.
le-mark 31 minutes ago [-]
But weren’t you GI on your own, before ai? Don’t sell yourself short bro! You got this!
UpsideDownRide 5 hours ago [-]
Ever is such a strong word.
bantunes 4 hours ago [-]
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.
baxtr 5 hours ago [-]
And AGI is such an undefined word.
petesergeant 4 hours ago [-]
Ten years ago people would have unambiguously identified what we had today as AGI.
Jensson 4 hours ago [-]
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.
latentsea 3 hours ago [-]
This. I don't know why people think the goalposts have moved.
petesergeant 20 minutes ago [-]
Ten years ago, AGI implied general intelligence, as opposed to ML models that had learned specific tasks. It meant a model that could reliably zero-shot problems you threw at it to human level without being specific models trained for that task. As recently as 2024, DeepMind's framework had:
> a Competent AGI must have performance at least at the 50th percentile for skilled adult humans on most cognitive tasks
and "emerging AGI" as
> "equal to or somewhat better than an unskilled human"
The moving the goalposts here is people saying it has to outperform humans on literally every task to be AGI. We have artificial general intelligence by any reasonable definition; people here are complaining we don't have super-intelligence.
xpct 2 hours ago [-]
What does that even mean? They would have tried the models, noticed their limitations, and decide it's not AGI. Same as today.
hsuduebc2 3 hours ago [-]
Two hundred years ago people would have unambiguously identified what we had today as mAGIc.
busssard 2 hours ago [-]
thats true even before GPT
hsuduebc2 2 hours ago [-]
I suppose that talking machine wouldn't be that surprising for them in the overall bundle of magic and miracles.
whilenot-dev 4 hours ago [-]
Unambiguously?
vladimirralev 5 hours ago [-]
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.
saithound 4 hours ago [-]
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.
amelius 4 hours ago [-]
How long until people switch from iOS or MacOS to ClaudeOS?
The downfall of Apple may be closer than people think.
willsmith72 3 hours ago [-]
how do i bet against that?
amelius 2 hours ago [-]
Send money to Apple.
jorisw 2 hours ago [-]
Buy AAPL
amelius 4 hours ago [-]
> 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.
PaulRobinson 2 hours ago [-]
"sharing" their knowledgebase?
Nobody "shared".
jen729w 4 hours ago [-]
> including the ops
Citation needed.
le-mark 1 hours ago [-]
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.
dingus-334257 4 hours ago [-]
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".
m-i-l 3 hours ago [-]
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, disruptive 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 to dig in areas with known gold deposits.
jstummbillig 33 minutes ago [-]
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.
bitmasher9 17 minutes ago [-]
[dead]
dofm 14 hours ago [-]
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?
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.
aenis 2 hours ago [-]
I think there is already one: ODE, a joint venture of sorts between Blackrock and Anthropic, if memory serves.
As for the cut, I am sure they will try. Where I work we have had a few projects that were built entirely with models - not a single line written or read by humans. One of them is now the fastest growing money maker for my company, reaching 89M of revenue on about 9% margin in 2 months of its existence, and growing.
It cost roughly 40k in tokens to build, 7 weeks from the first prompt to first production revenue, and was built and is being operated by 1.5 guys. Its a fantastic bang for buck for us, as previously such complex automations would have been impossible to build economically.
There will be an attempt to get a deeper cut of that value. We already see this, for instance, in Meta charging by message on Whatsapp from Oct 1, raising the costs for AI-powered chatbots delivered to consumers via whatsapp by 10-15x easily. More to come for sure.
angelos_7 2 hours ago [-]
Can you share more in the product? 9% margin also doesnt sound great imo
aenis 2 hours ago [-]
Customer service industry, roughly. Its a low margin business to begin with. We were able to expand into a new area, where we previously couldn't operate at a profit. We hired 3 people to run the new business, built them a tool, and it now runs pretty well and above our normal margins.
oblio 2 hours ago [-]
> Its a fantastic bang for buck for us, as previously such complex automations would have been impossible to build economically.
If you really did it with 1.5 people and it is profitable, you will have 1000 clones in 1 year. The only moats will be first mover advantage (slim), connections (all right) and the possible secrecy of how much you're making (very slim).
aenis 2 hours ago [-]
I am not arguing it. But if we didn't do it, others would. And I dont worry about 1000 clones, I worry about our key competitors building 3.
Edit: I'd also argue its not as simple as vibing a trivial solution. It took deep domain knowledge, which is not in the public domain, and is built on decades of operating this sort of thing manually, and integrating it with dozens of external systems that help make this into a moneymaker. I am not saying its impossible to replicate, but it's not something one can replicate by merely watching it function.
oblio 11 minutes ago [-]
Domain knowledge is definitely a moat. I'd argue another moat is surprisingly, if scaling is hard or even impossible. The biggest sharks just won't bother.
Bluestein 5 hours ago [-]
Forward Deployed Entrepreneurs.-
AquiGorka 56 minutes ago [-]
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.
kolinko 5 hours ago [-]
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.
illwrks 12 minutes ago [-]
As the saying goes… the devil is in the details.
_bobm 2 hours ago [-]
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.
CharlieDigital 2 hours ago [-]
these aren't mutually exclusive.
they can capture even more human trajectories by also owning all the data on how people do things in software.
_bobm 2 hours ago [-]
I agree.
le-mark 48 minutes ago [-]
[dead]
qnleigh 2 hours ago [-]
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.
HarHarVeryFunny 46 minutes ago [-]
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.
tim333 9 minutes ago [-]
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.
mcv 17 minutes ago [-]
They're selling the shovels to the gold miners.
altcognito 15 hours ago [-]
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.
TheOtherHobbes 3 hours ago [-]
It's common knowledge that ideas are worthless and only execution matters.
That was somewhat true when execution was time-consuming and expensive.
But original ideas are very far from worthless. They're very rare, because understanding domains and relationships at a deep level is a rare skill.
Meanwhile AI makes execution much cheaper and easier than it used to be.
thelastgallon 2 hours ago [-]
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.
hackyhacky 2 hours ago [-]
> and can never do AI.
How did you reach that conclusion? Apple has $62B just sitting around. They could hire as many AI people as they want and have Siri compete with the frontier models. They certainly can do AI.
I guess that are choosing not to do that because that's just not their business and they'd prefer to avoid the upcoming AI bloodbath. Why develop a search engine/social network/frontier AI when you can just use someone else's?
thelastgallon 1 hours ago [-]
It is not about hiring people, it is culture and inertia. You can hire the most brilliant people, yet they can't accomplish much if the culture isn't right. Google probably has better talent density than Anthropic and OpenAI, yet it can't compete[1]. Companies can do amazing things when the founder is around and sets a vision and culture. After that, its downhill. Has happened to all companies. They all go down. Apple is going down, but it is hard to see because it still has momentum from the founders charisma. Steve Jobs wouldn't have approved most of the products that Apple is selling now and allowed ads and enshittification.
[1] https://pravse.medium.com/the-maze-is-in-the-mouse-980c57cfd...: The way I see it, Google has four core cultural problems. They are all the natural consequences of having a money-printing machine called “Ads” that has kept growing relentlessly every year, hiding all other sins.
(1) no mission, (2) no urgency, (3) delusions of exceptionalism, (4) mismanagement.
PaulRobinson 2 hours ago [-]
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.
bushbaba 2 hours ago [-]
Amazon’s edge is logistics. That’s not something you can vibe code
lesuorac 1 hours ago [-]
Amazon’s edge is scale.
There are plenty of warehouse and delivery companies you could rent/pay in the short term that make logistics feasible.
m11a 14 hours ago [-]
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)
armchairhacker 3 hours ago [-]
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.
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.
psadri 14 hours ago [-]
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.
NormalGoat 14 hours ago [-]
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.
sumedh 29 minutes ago [-]
> They build the broad stuff themselves, like AI inside Excel or PowerPoint
Didnt OpenAI build a browser not just AI inside a browser?
TheOtherHobbes 3 hours ago [-]
The G in AGI suggests that not being specialised is the point.
The real reason is the models just aren't good enough.
Running a single successful fully automated business at scale would be a huge milestone and a legendary PR achievement, but the tech just isn't there yet.
ares623 2 hours ago [-]
Best I can do is Rust rewrites take it or leave it
mrheosuper 6 hours ago [-]
> 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.
Tryvrsakjo10 6 hours ago [-]
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.
Towaway69 6 hours ago [-]
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.
Tryvrsakjo10 6 hours ago [-]
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.
Towaway69 6 hours ago [-]
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.
Ylpertnodi 5 hours ago [-]
Good morals.
zahrevsky 13 hours ago [-]
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.
ricardobeat 6 hours ago [-]
But that’s the gist of the question, can’t their internal frontier models provide that infinite attention? That is what their PR implies.
surgical_fire 12 hours ago [-]
I thought the agents were largely autonomous, and should replace workers?
If labor is not your constraint, you wouldn't be diverting your specialization.
JMiao 14 hours ago [-]
idk they’ve created the most used and differentiating apps though
rpdillon 14 hours ago [-]
They aren't in the top 10 for either free or paid apps.
That actually makes me wonder if Apple apps are not included because they come pre-installed.
JMiao 14 hours ago [-]
i am referring to imessage, camera, photos, facetime, and so on
victorbjorklund 1 hours ago [-]
Why does the farmer not start a bakery if their grains are so good? And so on. Silly argument.
bunderbunder 58 minutes ago [-]
It is silly, but it matches the spirit of the AI hype that these companies themselves have promulgated. Not many farmers have claimed that their wheat is so great it knows how to mill and bake itself into high quality French pastry.
phoghed 12 minutes ago [-]
At this point we see way more complaining about alleged hype than we do real hype. Sam doesn’t even have to hype it anymore because there’s a million people who will do it for him just so they can complain about it.
Matl 45 minutes ago [-]
Actually, farmers owning other businesses that use farm produce as input is not super uncommon.
ffritz 1 hours ago [-]
Because a farmer is not backed by basically unlimited compute and can not one-shot prompt a bread to be baked automatically.
jbs789 1 hours ago [-]
Vertical integration is not silly. But you do need to figure out what you’re really good at. And for some people (companies) vertical integration makes sense and for others it does not.
aaronrobinson 33 minutes ago [-]
It detracts from their core business and they’re struggling with money as it is.
atraac 3 hours ago [-]
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.
simianwords 3 hours ago [-]
> They're selling shovels and pickaxes during a gold rush.
this is a thought terminating cliche. What you are implying is that AI will just go away in the future. That won't happen.
le-mark 19 minutes ago [-]
Oil is better analogy imo. But not as catchy. Intelligence is apparently something that just falls out of math. So pumping it out of the ground and distributing it is not free but it is a commodity. Similar to oil it will take time to build out the infrastructure to utilize it.
w4der 2 hours ago [-]
Neither gold nor pickaxes did, but both business went back to reasonable levels and valuations.
RunSet 44 minutes ago [-]
> That won't happen.
Speaking of thought-terminating cliches...
acd 1 hours ago [-]
Because
a) ai companies are already high valued.
b) the showles are not digging gold at the rate claimed
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.
dijit 4 hours ago [-]
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.
melbourne_mat 6 hours ago [-]
Being one of the premiere AI companies is much more exciting to investors than "running a company using AI" which everyone can do
Tryvrsakjo10 6 hours ago [-]
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.
ricardobeat 6 hours ago [-]
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.
plastic-enjoyer 6 hours ago [-]
Even after the singularity the almighty AI has to work to pay rent...
Terr_ 5 hours ago [-]
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.
euroderf 4 hours ago [-]
Does the grey goo need solar panels, or does it contains the requisite genes ?
pizza234 2 hours ago [-]
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.
chopin 2 hours ago [-]
That'd be great CEO's, however.
oblio 2 hours ago [-]
> but they don't see the big picture/think out of the box.
I know LLMs have some emergent properties. But at the the day they're regression/forecast machines. And those machines ultimately point to the mean, which is definitely in the box. Heck, it IS the box itself.
BerislavLopac 2 hours ago [-]
Why don't the shovel-sellers hire a bunch of people to dig for gold, instead of just selling shovels?
neonnoodle 2 hours ago [-]
In this analogy, NVDIA would be the shovelmonger.
digitaltrees 16 hours ago [-]
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)
creaktive 37 minutes ago [-]
Models aren’t THAT good, after all.
arjie 5 hours ago [-]
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.
izecube 4 hours ago [-]
really great analogy, it’s like selling shovels in a gold rush type of thing
tracerbulletx 6 hours ago [-]
Building software is only one part of building a business. There's a bottleneck in all of the other parts.
Ekaros 6 hours ago [-]
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.
starbugs 5 hours ago [-]
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.
le-mark 12 minutes ago [-]
> 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.
So much this! The only recourse is to hand them straight to ai to implement. And so it goes.
tikotus 6 hours ago [-]
Software might be solved, but not everything is solvable by software.
3 hours ago [-]
maxdo 2 hours ago [-]
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
meerita 2 hours ago [-]
Dario said that the objective of Anthropic is to become "the only company in the world". I think that answer your question.
antonvs 59 minutes ago [-]
That quote is hearsay from Gavin Baker of Atreides. He said he heard it from “trusted sources”.
paxy 15 hours ago [-]
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.
devin 15 hours ago [-]
You can just restate the question then to say: If the models are so good, why can't they run a business?
paxy 15 hours ago [-]
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.
argee 15 hours ago [-]
This is just a form of "if you're so smart, why aren't you rich?", isn't it?
ares623 2 hours ago [-]
$2T valuation good for a start
ReDress 4 hours ago [-]
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.
cmblsss 3 hours ago [-]
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
dubeye 58 minutes ago [-]
anthropic has record breaking revenue growth already, why complicate it
more users = more training data
Matl 35 minutes ago [-]
They're very good at 'adjusting' revenue, who knows what the actual truth is.
InsidiousWombat 14 hours ago [-]
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.
aryanthakor 3 hours ago [-]
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.
russx2 2 hours ago [-]
Can you elaborate? I've heard mixed opinions on pi/omp.
latentsea 3 hours ago [-]
Try it with Qwen2.5 then.
pacolove 6 hours ago [-]
Just like the people who tell you how to get rich in YouTube ads aren't actually rich.
Havoc 14 hours ago [-]
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.
janalsncm 14 hours ago [-]
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.
Havoc 14 hours ago [-]
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
JMiao 14 hours ago [-]
who will be in the bread line if it blows
13 hours ago [-]
pembrook 1 hours ago [-]
- 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
gofreddygo 15 hours ago [-]
reframed question - if their shovels are so good why dont they dig gold and sell gold themselves.
stingraycharles 15 hours ago [-]
I thought NVidia was the one selling shovels here, not OpenAI.
besterman23 15 hours ago [-]
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?
stingraycharles 14 hours ago [-]
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.
besterman23 14 hours ago [-]
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.
imtringued 5 hours ago [-]
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.
tayo42 14 hours ago [-]
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
besterman23 13 hours ago [-]
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.
nemo44x 2 hours ago [-]
It’s shovels all the way down. Nvidea is selling shovels to frontier model labs who are selling shovels to AI companies who are selling shovels to actual businesses who have nicer power point presentations, a lot more dashboards, and some inference driven workflows.
magarnicle 14 hours ago [-]
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.
purpleidea 2 hours ago [-]
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.
deadbabe 51 minutes ago [-]
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.
wewewedxfgdf 14 hours ago [-]
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.
throw20261022 15 hours ago [-]
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.
Kiro 4 hours ago [-]
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.
rkuodys 4 hours ago [-]
Wasn't spacex/x trying to do exactly that mid September?
thomasfromcdnjs 14 hours ago [-]
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.
hackernudes 9 hours ago [-]
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.
janalsncm 14 hours ago [-]
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.
Good4boothee 4 hours ago [-]
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?
willsmith72 3 hours ago [-]
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
mellosty 3 hours ago [-]
Not everyone trust them.
15 hours ago [-]
rgbrgb 14 hours ago [-]
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)
antaviana 14 hours ago [-]
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.
SugarReflex 14 hours ago [-]
Giving strong "if my grandmother had wheels she would have been a bike" vibes and I don't know why.
Good point, instead of wasting their compute in solving 100 years old math problems.
Spoiler alert: it's a sarcasm
nemo44x 2 hours ago [-]
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.
bitwize 2 hours ago [-]
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.
browningstreet 14 hours ago [-]
Starting a company is riskier than selling to companies who survived the “it’s hard to start a company” gauntlet.
HeavyStorm 15 hours ago [-]
Better to sell spades than mine for gold...
mikert89 14 hours ago [-]
Thats what they are doing, except with a unified model, not a seperate app for each one
shaolinspirit 54 minutes ago [-]
it would be called communism without sharing anything
haute_cuisine 13 hours ago [-]
If models are good, they should develop their own chips/memory.
jrflowers 14 hours ago [-]
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
dude250711 15 hours ago [-]
Why don't they simply run a quantitative hedge fund on the side?
dingdongditchme 4 hours ago [-]
Leopold Aschenbrenner tried this and got eaten by the wolves as far as I can tell...
ex-aws-dude 14 hours ago [-]
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?
randomNumber7 14 hours ago [-]
They wait and collect data from their future competitors first.
dspillett 3 hours ago [-]
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.
--------
Slightly more grounded: the models aren't that good, at least not yet, despite what marketing would like you to believe.
Retr0id 14 hours ago [-]
Selling tokens is what scales best right now.
Geste 9 hours ago [-]
Big if in your question.
mattmaroon 3 hours ago [-]
“If owning a McDonald’s is so good, why sell franchises?”
mindwok 14 hours ago [-]
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.
Rodmine 15 hours ago [-]
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.
Cameri 12 hours ago [-]
Do you really believe that inference is their only service? Come on.
nickphx 3 hours ago [-]
because the nondeterministic black box of bullshit is incapable.
RohaanXD 2 hours ago [-]
[flagged]
krisgenre 3 hours ago [-]
[dead]
salemh 15 hours ago [-]
Why aren't they vibe coding millions of dollars of licensing costs away?
Why Even Anthropic Can’t Vibe-Code Away Salesforce
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.
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 .
It's not like they're trying, they are trying very hard
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.
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.
Although the point would be equally valid if they were OpenAI consultants. (Imagine paying twice for the help: once for the consultant and once for the tokens.)
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.
This is a huge problem, why is it like this
Investment isn't debt.
Presumably there are penalties if OpenAI were to cancel that order (I am confident that Oracle's army of lawyers made sure to include that). That's the unmovable rock on OpenAI's books, not the data center.
Not a useful term, here.
AIUI, the building is funded by making the people who order it part owners in the new data center company. Not sure and I don’t care enough to find out; clarification welcome.
...yet.
One of the biggest AI investors.
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.
In part it is like this because they've already borrowed so much.
Investment isn't debt.
No they don't.
A company has legal obligation to pay loans at the agreed rates.
There is legal obligation that defines rates of return beyond "acting in shareholder interest" (and OpenAI is a public benefit corporation so even this is reduced).
Because it's an investment it is risk capital. They won't be happy if they don't get a return but their return is part ownership in the company, not a legal contract giving an income stream.
That's what is driving up the cost of debt and teetering some of these companies into junk status.
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.
No.
> If VC provide you funds, there is an expectation of returns, otherwise the board would vote you out.
A person might get replaced as CEO but the company has no financial obligation to the investors.
A loan means the company does.
Legally they are dramatically different.
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.
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.
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.
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
Down the chain you see what you need to do because you work directly with it everyday.
Neither would be easy for either to do
Didn’t DeepSeek just disabuse us of that notion?
> …with overall revenue of US$38 per GPU-hour (at valley pricing)
https://github.com/deepseek-ai/DeepInfer/blob/main/doc/infer...
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.
> a Competent AGI must have performance at least at the 50th percentile for skilled adult humans on most cognitive tasks
and "emerging AGI" as
> "equal to or somewhat better than an unskilled human"
The moving the goalposts here is people saying it has to outperform humans on literally every task to be AGI. We have artificial general intelligence by any reasonable definition; people here are complaining we don't have super-intelligence.
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.
The downfall of Apple may be closer than people think.
They don't have to do it openly.
Nobody "shared".
Citation needed.
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.
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.
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.
As for the cut, I am sure they will try. Where I work we have had a few projects that were built entirely with models - not a single line written or read by humans. One of them is now the fastest growing money maker for my company, reaching 89M of revenue on about 9% margin in 2 months of its existence, and growing.
It cost roughly 40k in tokens to build, 7 weeks from the first prompt to first production revenue, and was built and is being operated by 1.5 guys. Its a fantastic bang for buck for us, as previously such complex automations would have been impossible to build economically.
There will be an attempt to get a deeper cut of that value. We already see this, for instance, in Meta charging by message on Whatsapp from Oct 1, raising the costs for AI-powered chatbots delivered to consumers via whatsapp by 10-15x easily. More to come for sure.
If you really did it with 1.5 people and it is profitable, you will have 1000 clones in 1 year. The only moats will be first mover advantage (slim), connections (all right) and the possible secrecy of how much you're making (very slim).
Edit: I'd also argue its not as simple as vibing a trivial solution. It took deep domain knowledge, which is not in the public domain, and is built on decades of operating this sort of thing manually, and integrating it with dozens of external systems that help make this into a moneymaker. I am not saying its impossible to replicate, but it's not something one can replicate by merely watching it function.
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, 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.
they can capture even more human trajectories by also owning all the data on how people do things in software.
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.
I doubt there are very many companies that an LLM could start/run outside of the obvious few like custom T-shirts.
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.
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.
That was somewhat true when execution was time-consuming and expensive.
But original ideas are very far from worthless. They're very rare, because understanding domains and relationships at a deep level is a rare skill.
Meanwhile AI makes execution much cheaper and easier than it used to be.
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.
How did you reach that conclusion? Apple has $62B just sitting around. They could hire as many AI people as they want and have Siri compete with the frontier models. They certainly can do AI.
I guess that are choosing not to do that because that's just not their business and they'd prefer to avoid the upcoming AI bloodbath. Why develop a search engine/social network/frontier AI when you can just use someone else's?
[1] https://pravse.medium.com/the-maze-is-in-the-mouse-980c57cfd...: The way I see it, Google has four core cultural problems. They are all the natural consequences of having a money-printing machine called “Ads” that has kept growing relentlessly every year, hiding all other sins.
(1) no mission, (2) no urgency, (3) delusions of exceptionalism, (4) mismanagement.
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.
There are plenty of warehouse and delivery companies you could rent/pay in the short term that make logistics feasible.
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)
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.
Didnt OpenAI build a browser not just AI inside a browser?
The real reason is the models just aren't good enough.
Running a single successful fully automated business at scale would be a huge milestone and a legendary PR achievement, but the tech just isn't there yet.
Not everything, but a company can be specialized in a lot of different things, Samsung for example, or megacorp in Japan.
That’s the other side of diversification: undercutting your competition until they go out of business. Then prices are raised again.
If labor is not your constraint, you wouldn't be diverting your specialization.
https://apps.apple.com/us/iphone/charts/36
That actually makes me wonder if Apple apps are not included because they come pre-installed.
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.
this is a thought terminating cliche. What you are implying is that AI will just go away in the future. That won't happen.
Speaking of thought-terminating cliches...
Ie over hype see the Hype cycle https://en.wikipedia.org/wiki/Gartner_hype_cycle
They’re chasing massive markets strategically, not trying to brute force small ones.
(and diversified risk)
a better reason might be that people would not want to use OpenAI because they might be sherlocked.
[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 can tell you with 100% certainty that they will pay rent, because they are us.
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.
I know LLMs have some emergent properties. But at the the day they're regression/forecast machines. And those machines ultimately point to the mean, which is definitely in the box. Heck, it IS the box itself.
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.
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.
So much this! The only recourse is to hand them straight to ai to implement. And so it goes.
And they already killed or make existence of many companies not viable , def 1000+ were killed
But, yeah and indeed, it probably takes more than just technical abilities to start a company.
more users = more training data
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.
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.
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.
...a dubious proposition except this time there is a small but real chance it may be actual magic
- 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
NVidia is good at making the shovels, and sticks to that.
Google is doing it successfully to the point where they only let you rent their shovels and never let you buy them.
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.
The counter-argument is that the models might make business ideas just as fungible as anything else.
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.
They will go broke running 100 companies unprofitably until they attain enough market share to be dominant in their respective fields.
Not feasible.
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.
They're doing the other thing too via numerous startup acquisitions.
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.
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?
I don't see any evidence that it can build a business
https://www.ft.com/content/df70bf20-e809-48d0-8485-f8f514a7f...
Spoiler alert: it's a sarcasm
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.
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.
--------
Slightly more grounded: the models aren't that good, at least not yet, despite what marketing would like you to believe.
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.
Why Even Anthropic Can’t Vibe-Code Away Salesforce
https://www.salesforceben.com/why-even-anthropic-cant-vibe-c...