So "boring" ? Definitely not.
So "boring" ? Definitely not.
from my recollection, post-FB $75B+ market cap consumer tech companies (excluding financial ones like Robinhood and Coinbase) include:
Uber, Airbnb, Doordash, Spotify (all also have ~$1bn+ monthly revenue run rate)
I propose oAI is the first one likely to enter the ranks of Apple, Google, Facebook, though. But it's just a proposal. FWIW they are already 3x Uber's MAU.
As Jobs said about Dropbox, music streaming is a feature not a product
Hyperbole to say no major consumer tech brands have launched for decades
I would be shocked if OpenAI was not in a similar (or worse) position.
Originally Netflix was a single tier at $9.99 with no ads. As ZIRP ended and investors told Netflix its VC-like honeymoon period was over - ads were introduced at $6.99 and the basic no ad tier went to $15.99 and the Premium went to 19.99.
Currently Netflix ad supported is $7.99, add free is $17.99 and Premium is $24.99.
Mapping that on to OpenAI pricing - ChatGPT will be ~$17.99 for ad supported, ~$49.99 for ad free and ~$599 for Pro.
But say you're correct, and follow the reasoning from there: posit "All frontier model companies are in a red queen's race."
If it's a true red queen's race, then some firms (those with the worst capital structure / costs) will drop out. The remaining firms will trend toward 10%-ish net income - just over cost of capital, basically.
Do you think inference demand and spend will stay stable, or grow? Raw profits could increase from here: if inference demand 8x, then oAI, as margins go down from 80% to 10%, would keep making $10bn or so a year in FCF at current spend; they'd decide if they wanted that to go into R&D or just enjoy it, or acquire smaller competitors.
Things you'd have to believe for it to be a true red queen's race:
* There is no liftoff - AGI and ASI will not happen; instead we'll just incrementally get logarithmically better.
* There is no efficiency edge possible for R&D teams to create/discover that would make for a training / inference breakaway in terms of economics
* All product delivery will become truly commoditized, and customers will not care what brand AI they are delivered
* The world's inference demand will not be a case of Jevon's paradox as competition and innovation drives inference costs down, and therefore we are close to peak inference demand.
Anyway, based on my answers to the above questions, oAI seems like a nice bet, and I'd make it if I could. The most "inference doomerish" scenario: capital markets dry up, inference demand stabilizes, R&D progress stops still leaves oAI in a very, very good position in the US, in my opinion.
Futures like that are why Anthropic and oAI put out stats like how long the agents can code unattended. The dream is "infinite time".
Brand loyalty and users not having sufficient incentive by default to switch to a competitor is something else. OpenAI has lost a lot of money to ensure no such incentive forms.
Moats, as noted in Google's "We Have no Moat, and Neither Does OpenAI" memo that made the discussion of moats relevant in AI circles, has a specific economic definition.
https://www.goodreads.com/book/show/32816087-7-powers
It has branding as one of the seven and uses coca cola as an example.
You may not see it, but OpenAI’s brand has value. To a large portion of the less technical world, ChatGPT is AI.
Comparing "brand moat" in real-world restaurant vs online services where there's no actual barrier to changing service is silly. Doubly silly when they're free users, so they're not customers. (And then there are also end-users when OpenAI is bundled or embedded, e.g. dating/chatbot services).
McDonald's has lock-in and inertia through its franchisees occupying key real-estate locations, media and film tie-ins, promotions etc. Those are physical moats, way beyond a conceptual "brand moat" (without being able to see how Hamilton Wright Helmer's book characterizes those).
In Europe, most companies and Gov are pushing for either mistral or os models.
Most dev, which, if I understand it correctly, are pretty much the only customers willing to pay +100$ a month, will change in a matter of minutes if a better model kicks in.
And they loose money on pretty much all usage.
To me a company like Antropics which mostly focus on a target audience + does research on bias, equity and such (very leading research but still) has a much better moat.
It has 20m paid users and ~ 780m free users. The free users are not at all sticky and can and will bounce to a competitor. (What % of free users converted to paid in 2025? vs bounced?) That is not a moat. The 20m paid users in 2025 is up from 15.5m in 2024.
Forget about the free tier users, they'll disappear. All this jousting about numbers on the free tier sounds reminiscent of Sun Microsystems chirpily quoting "millions and billions of installed base" back in the Java wars, and even including embedded 8-bit controllers.
For people saying OpenAI could get to $100bn revenue, that would need 20m paid users x $5000/yr (~ the current Pro $200/mth tier), but it looks they must be discounting it currently. And that was before Anthropic undercut them on price. Or other competitors.
>The free users are not at all sticky and can and will bounce to a competitor.
If you really believe this, that just shows how poor your understanding of the consumer LLM space is.
As it is, ChatGPT (the app) spends most of its compute on Non work messages (approx 1.9B per day vs 716 for Work)[0]. First, from ongoing conversations that users would return to, to the pushing of specific and past chat memories, these conversations have become increasingly personalized. Suddenly, there is a lot of personal data that you rely on it having, that make the product better. You cannot just plop over to Gemini and replicate this.
[0] https://www.nber.org/system/files/working_papers/w34255/w342...
- your comment about lock-in for existing users only applies historically to existing users.
- Sora 2 is a major pivot that signals what segment OpenAI is/isn't targeting next: Scott Galloway was saying today it's not intended to be used by 99% of casual users; they're content consumers, only for content creators and studios.
And that's nice for them.
- your comment about lock-in for existing users only applies historically to existing users.
ChatGPT is the brand name for consumer LLM apps. They are getting the majority of new subscribers as well. Their competitors - Claude, Gemini are nowhere near. chatgpt.com is the 5th most visited site on the planet.
You're aware they already announced they'll add ads in 2026.
And the circular trades are already rattling public markets.
How do they monetize users on the base tier, to any extent? By adding e-commerce? And once they add ads how do they avoid that compromising the integrity of the product?
Netflix introduced ads and it quickly became their most popular tier. The vast majority of people don't care about ads unless it's really obnoxious.
Training costs can be brought down. New algorithm can still be invented. So many headrooms.
And this is not just for OpenAI. I think Anthropic and Gemini also have similar room to grow.
They have no moat, their competitors are building equivalent or better products.
The point of the article is that they are a bad business because it doesn't pan out long term if they follow the same path.
OpenAI didn't build the delivery system they built a chat app.
I also wouldn't say "democratized", more like popularized or made accessible. Though I'm more nitpicking here.
But at this point - there's nothing really THAT special about them compared to their competition.
As a player for over 20 years this will be a core memory of OpenAI. Along with not living up to the name.
Let’s say Google or Anthropic release a new model that is significantly cheaper and/or smarter that an OpenAI one, nobody would stick to OpenAI. There is nearly zero cost to switching and it is a commodity product.
Anecdata but even in work environments I hear mostly complaints about having to use Copilot due to policy and preferring ChatGPT. Which still means Copilot is in a better place than Gemini, because as far as I can tell absolutely nobody even talks about that or uses it.
The human side is impossible to cost ahead of time because it’s unpredictable and when it goes bad, it goes very bad. It’s kind of like pork - you’ll likely be okay but if you’re not, you’re going to have a shitty time.
The AI market, much like the phone market, is not a winner take all. There's plenty of room for multiple $100B/$T companies to "win" together.
This is not at all how the consumer phone market works. Price and “smarts” are not only factor that goes into phone decisions. There are ecosystem factors & messaging networks that add significant friction to switching. The deeper you are into one system the harder it is to switch.
I don't think this is true over the short to mid term. Apple is a status symbol to the point that Android users are bullied over it in schools and dating apps. It would take years ti reverse the perception.