Ask HN: If the models are so good, why doesn't OpenAI just start 100 companies? (self)

The Firm is confederated.

Oh wait.

The former Starbucks CEO is a classic example. His infamous interview with Cramer on CNBC is the textbook of what it looks like when some McKinsey consultant gets actually put in charge. It was a total shitshow.

Likely succeeded at pontificating to CEOs via PPT, but actually being CEO? Not so much.

Also the reputation is not minor, the human can take out loans, or take a withdrawal out from their social capital by telling people that they are AI enabled and selling AI to other (presumably) non-AI people.

It's not all just GPUs and Tokens, it can't be, there needs to be some mixing with other resources in order to bake a value cake. While pure token cakes might be very yummy (for some consumers who like pure slop), by mixing GPUs with human brains, a wider space of yummy hybrid cakes can be explored, which even more consumers would enjoy (those who like partial slop).

Even drug manufacturers need retailers who use their personal connections to gain trust, and who put their criminal record on the line.

Do they? Haven't Google and others been proving that wrong for almost 30 years?

Is they though?

The glossy magazines read by C-suite is the slick marketing part, not the actual product.

This is silly, these companies are owned and run by some of the most connected and powerful people on the planet, who also own and run dozens of other companies that produce things.

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

I don't even know what this means. They choose to hire who they choose to hire, and they can continue to hire as long as they wish. It's like saying that the reason I'm not a marathon runner is because I only own Oxfords and flip-flops, not running shoes.

I have absolutely no idea how this could be the "sort of obvious answer." I'm surprised so many people thought it was worth a response. There's no answer here. Some of these sentences don't even make sense.

OpenAi is also spinning up and acquiring companies. DeployCo, Orchestra Bio, io Products Inc.

Those are very much not the same.

Sorry, this is not even close to being an answer let alone an obvious answer. The main reason is because 'reality has a surprising amount of detail' (read the excellent blog post if you have). There is a huge difference between doing some analysis, framework, and outlining recommendations on a slide vs. generating business value in the real world. The real world is messy, a complex and dynamic adaptive system, with tons of details where small decisions add up.

Put a feature team in a strong company / startup and put them up against a top consultant on a real world scenario to ship something and generate real world value/uusage and you will get the answer why.

It's a serious bit of hypocrisy posed by OpenAI here, and it's telling that the AI is much more limited that the narrative of 'AGI' would have us believe.

OAI and Anthropic have massive budgets they should be able to expand, were AGI actually AGI.

That’s especially true if it’s an artificial gold rush that you created yourself.

They also serve as a part-time strategy group for the company. The company couldn’t afford that quality of people full time and they wouldn’t have as much experience as at a consultancy. And having temporary people not beholden to a superior might result in more honest reports.

So, it’s not necessarily flimflam. But I do worry a group of people who determine a company’s strategy and rarely stick around to implement it and measure it’s end result.

This is a huge problem, why is it like this

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.

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.

If they don't make it, there will be plenty of time to mine through their dataset for business ideas to sell to other people as they liquidate. Think of the Spirit Airlines dataset that was just sold.

This is the most insane perspective, it's like you have now idea what is happening across the industry. In you fantasy world here, are you saying devs are just yeeting slop into production, no debugging, no profiling, no code review, just prompt to prod? Because that's not happening.

There's no reason for OpenAI/Google/Anthropic/etc to start other software businesses because "LLMs" will be the only software that anybody will ever pay for.

Why would you have a different "app" to do something when you can just do it all in Claude or Gemini or ChatGPT? We'll be there soon enough.

The perpetual state of being in the inflection point upon which entire industries are just... killed.

Of course you shouldn't just rely on AI that's consumed every MBA book to give you all of your business advice. Sometimes the textbook response is not always the best response.

That overhyped thing that never did anything well and everybody that used them regretted it later? Yeah, hyped things tend to die once the money used to hype them ends.

> Any data visualization tools

Microsoft killed them with anticompetitive practices. It helps that every single one of them tried very hard to kill themselves by being as hostile as possible.

> Data integration tools all kind of crm to crm to erp to something else

Yep, everybody writes those in Python nowadays. Apache is a great market killer, the best kind of market killer.

IDEs will be moot when I die. Even with tests and code gen, I still debug and verify code before shipping to QA.

This is a wild take.

Nerds also underestimate how how social people are. I can guarantee you there are whole segments of the economy that will not be fully decimated solely because they don't actually give a shit if an AI can do the job because the job is 99% clout and relationships.

Agent swarms, you say? Perhaps. But I don't think we're there quite yet. At least, we're not seeing it manifest.

Hence this is also why although AI is writing the code now, it doesn't replace the companies or build entire large scale products without human oversight.

Add to that the fact that the AI itself is going to be more or less a commodity as well and you wonder where all the profits are meant to come from.

LLM makes may make more money before their tech really works than after.

>I think this is basically what it will be for most knowledge work, knowledge workers are so grossly overpaid compared to the energy they consume, and AI will rectify that. This explains why the Chinese are giving the (much more moderate resources to train) models away for free. They love to see deflationary economics in the US.

https://geohot.github.io/blog/jekyll/update/2026/06/11/ai-wi...

Neither would be easy for either to do

They don't have to do it openly.

Citation needed.

Nobody "shared".

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.

The barrier is often that the investors aren't fond of the heavy investment and risks involved. Using AI to generate some app would presumably not have the same level of concern.

But where the business model lands we simply have no idea of currently because the future is in the future.

Except they're not. Those shovel sellers weren't losing $2 for every $1 shovel they sold.

They also have a market (https://andonlabs.com/market) and a radio (https://andonlabs.com/radio)

If labor is not your constraint, you wouldn't be diverting your specialization.

Not everything, but a company can be specialized in a lot of different things, Samsung for example, or megacorp in Japan.

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.

A machine with infinite attention and infinite knowledge probably could specialize in everything.

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.