[matchagaucho]

As someone working in the enterprise space with OAI, this still feels like we're in the top of the first inning.

Many teams remain anchored on equating AI with chat experiences, while a growing share of enterprise value is emerging from leasing compute clusters to run agentic workloads in containerized environments.

OpenAI has built a cloud-first architecture that supports this model. The desktop experience and applications are sexy, but enterprise usage will likely skew heavily toward asynchronous, background processing.

[mandevil]

I know that people keep saying "we're early on here", but I take it as a negative signal that people keep thinking we are in the early innings here. Compared to previous generations of technology change, a great deal of time has passed, it should be a bit disconcerting that no one seems to have found a way to make money out of this yet.

Look at previous killer apps- they came out quickly and were raking in money very quickly. The Apple II went on sale on June 10th, 1977. Visicalc went on sale October 17th, 1979- 860 days separate the two. Apple IPO'd in 1980 with a 21% operating margin! Netscape Navigator 1.0 released December 15th 1994, Amazon.com made its first sale July 16th 1995- 214 days later. AMZN IPO'd May 15th 1997, 883 days after Netscape 1.0 released to the public (they had raised <10 million dollars to that point, but chose not to have a profit because they kept re-investing all of their profit into expanding the business).

We are already 1232 days since ChatGPT 1.0. So we're about 50% farther along than either of those killer apps. No one has figured out as good a business model for Generative AI as either of those were.

To use the other great technology transformation of the past 50 years, cell phones, I have a bit of trouble figuring out the right comparison to ChatGPT 1.0. I can work backwards from today to ChatGPT 1.0 opening up to the public, that's about the difference from the iPhone 3G (the first one with an appstore, the real killer app) to the launch of the Motorola Razr, to give you an idea of how fast mobile technology moved.

Do note that the Razr and the iPhone, like Visicalc, the Apple II, and Netscape 1.0 were hugely profitable for their companies, in a way that no one has demonstrated with Generative AI. Amazon is a bit of a special case, but they were not raising money, they were just re-investing cash that was being thrown off not as profits but into expanding the business. I don't believe that any AI company is generating cashflow the way that Amazon was in 1997, and the other companies mentioned here were GAAP-profitable.

[grtteee]

Most people don’t want to accept and believe that the only viable revenue stream is selling tokens in relation to software development.

All the other stuff is nice… but you will continue to be money losing and eventually die.

Now you can’t come out and say this because there’s a whole bunch of investments that depend on hype - think about the robotics nonsense.

[mandevil]

Is it actually profitable? That the presumed market leader, Anthropic, changed their business model just today to kill off their buffet monthly plans and switch to a la carte for Enterprise makes me doubt they are making money off of selling tokens to software developers.

[grtteee]

I never commented on profitability, only revenue.

And I’m referring to selling tokens to enterprises that produce software.

[Ekaros]

There is some revenue in copywriting, translation and generating images. But that is probably 20 per month per seat enterprise plans with limited use. With the possible cost of interface varying enough to have actual marginal costs...

[matchagaucho]

"previous killer apps" - exactly. That's the point. Everyone is anchored in AI as being the next desktop app. It's not.

We're only using 1% of what these models will ultimately do when they're running 24/7 as utilities serving new economic models.

There just isn't enough compute right now to realize the larger monetization strategies.

[prescriptivist]

On top of that, the APIs/Tools/Function Calls into the real world don't exist yet. But consumer products are going to start eventually exposing functionality to these LLMs. By that time, I wonder if we'll all have an edge-inference box sitting in every one of our houses that we buy from a consumer products company like Apple or from Amazon, or directly from OpenAI or Anthropic. These little brains will be the low latency central nervous system of a lot of things in our homes, and gateways to the larger models in the cloud. Or at least that's how I imagine it sorting out in the future.

[mandevil]

Previous generations of technological change of the calibre we are told AI will be also required major changes to the real world and new products to be built: new cell towers had to be constructed, fibre cables laid, data centers built, personal computers produced, warehouses established. And software needed to be fundamentally rewritten to support each of these generations too. And yet the companies doing that in those previous generations managed to produce huge profits significantly faster than Generative AI has.

That's my biggest concern with it, I don't see the business case closing anywhere, and without businesses that actually make money all the technology in the world doesn't actually do anything.

[prescriptivist]

> And yet the companies doing that in those previous generations managed to produce huge profits significantly faster than Generative AI has.

Have you considered a simple answer to this inconsistency? The market and investors does not demand that these AI companies make a profit. The only reason companies are expected to make profits is because either those who own shares in the company expect it, or those willing to invest in a company expect it.

[matchagaucho]

More likely people will delegate their agents to run in the cloud.

Edge AI on iPhone, however... many potential applications around vision, hearing, interpreting your surroundings in real-time.

[lelanthran]

> There just isn't enough compute right now to realize the larger monetization strategies.

How can this be relevant? Why isn't the compute we have available right now sufficient for turning a profit?

Is this another one of those "We lose money on each sale but make it up in volume" things?

I mean, if much much larger investments are needed before current LLM providers can turn a profit, that's not a good indicator that they have any sort of sustainable business, is it?

[matchagaucho]

Profit is not the goal in large transformational tech cycles.

See Bezos' playbook for Amazon. They weren't profitable for years.

[prescriptivist]

Comparing the IPO market today to the IPO market in the late 90s is not very instructive. You could have IPO'd a lemonade stand in 1998 and raised $10 million.

[mandevil]

I'm using that only for AMZN because they seem to have made a choice to not turn a profit and instead to expand their business. The other companies I mentioned were directly profitable by this point in their respective revolutions, except for Amazon, where I'm using the IPO as proof that they had a sustainable business, even if it wasn't precisely profitable- they were generating enough cash to be profitable, they just chose to reinvest it into the business. I don't see any evidence that any of the major Generative AI companies are in that position or the position that Apple, Netscape, Motorola etc. were in.

And that's the weird one, all of the other examples I provided were booking real profits by this point in their technology cycle.

[nl]

I think that fact that IPOs have grown slower over the years is more about larger VC markets where they can fund valuations up to hundreds of billions rather than something to do with adoption.

As you note, Netscape and Amazon IPOed fairly quickly.

Google took 6 years (1998 to 2004)

Facebook took 8 years (2004 to 2012)

Alibaba Group took 15 years (1999 to 2014)

Claude Code is at $30B annual recurring revenue, and it launched in Feb 2025, and OpenAI at $25B (although they measure partner revenue differently). By comparison the iPhone make $630M revenue in the 12 months after it was launched.

[lelanthran]

> Claude Code is at $30B annual recurring revenue, and it launched in Feb 2025, and OpenAI at $25B (although they measure partner revenue differently). By comparison the iPhone make $630M revenue in the 12 months after it was launched.

What does revenue have to do with it? Companies usually want to IPO with a decent profit margin showing on the books, revenue doesn't usually come into it.

[nl]

> Companies usually want to IPO with a decent profit margin showing on the books, revenue doesn't usually come into it.

Untrue.

Read what the OP said about Amazon.

And Figma - the most recent high-profile IPO I could think of - isn't profitable.