[hijodelsol]

If you read any work from Ed Zitron [1], they likely cannot remain sustainable. With OpenAI failing to convert into a for-profit, Microsoft being more interested in being a multi-modal provider and competing openly with OpenAI (e.g., open-sourcing Copilot vs. Windsurf, GitHub Agent with Claude as the standard vs. Codex) and Google having their own SOTA models and not relying on their stake in Anthropic, tarrifs complicating Stargate, explosion in capital expenditure and compute, etc., I would not be surprised to see OpenAI and Anthropic go under in the next years.

1: https://www.wheresyoured.at/oai-business/

[vessenes]

I see this sentiment everywhere on hacker news. I think it’s generally the result of consuming the laziest journalism out there. But I could be wrong! Are you interested in making a long bet banking your prediction? I’m interested in taking the positive side on this.

[hijodelsol]

While some critical journalism may be simplistic, I would not qualify it as lazy. Much of it is deeply nuanced and detail-oriented. To me, lazy would be publications regurgitating the statements of CEOs and company PR people who have a vested interest in making their product seem appealing. Since most of the hype is based on perceived futures, benchmarks, or the automation of the easier half of code development, I consider the simplistic voices asking "Where is the money?" to be important because most people seem to neglect the fundamental business aspects of this sector.

I am someone who works professionally in ML (though not LLM development itself) and deploys multiple RAG- and MCP-powered LLM apps in side businesses. I code with Copilot, Gemini, and Claude and read and listen to most AI-industry outputs, be they company events, papers, articles, MSM reports, the Dwarkesh podcast, MLST, etc. While I acknowledge some value, having closely followed the field and extensively used LLMs, I find the company's projections and visions deeply unconvincing and cannot identify the trillion-dollar value.

While I never bet for money and don't think everything has to be transactional or competitive, I would bet on defining terms and recognizing if I'm wrong. What do you mean by taking the positive side? Do you think OpenAI's revenue projections are realistic and will be achieved or surpassed by competing in the open market (i.e., excluding purely political capture)?

Betting on the survival of the legal entity would likely not be the right endpoint because OpenAI could likely be profitable with a small team if it restricted itself to serving only GPT 4.1 mini and did not develop anything new. They could also be acquired by companies with deeper pockets that have alternative revenue streams.

But I am highly convinced that OpenAI will not have a revenue of > 100 billion by 2029 while being profitable [1] and willing to take my chances.

1: https://www.reuters.com/technology/artificial-intelligence/o...

[vessenes]

OK, I like this so far, and I accept the critique on lazy. I might restate to ‘knee jerk uninformed and poorly reasoned journalism’.

Do I think OpenAI’s revenue projections are realistic? I’m aware of leaks that say $12.5bn in 2025 and $100+bn in 2029. Order of magnitude, yes, I think they’re realistic. Well, let me caveat that. I believe they will be selling $100+bn at today’s prices in 2029.

Is this based only/largely on political capture? Don’t know or care really, I’m just tired of (formerly called lazy) journalism that gets people confidently wrong about the future telling everyone OpenAI is doomed.

On the Reuters story — to be clear, OpenAI’s current plans mean that being cash flow positive in 2029 would be a bad thing for the company. It would mean they haven’t gotten investment to the level they think is needed for a long term winning play, and will have been forced to rely on operating cash flow for growth. In this market, which they postulated was winner take all, and now propose is “winner take most” or “brand matters and TAM is monstrous”, they need to raise money to compete with the monstrous cash flow engines arrayed against them: Meta, Google, and likely some day Apple and possibly Oracle. On the flip side, they offer a pretty interesting investment: If you believe most of the future value of GOOG or META will come from AI (and I don’t necessarily believe this, but a certain class of investors may), then you could buy that same value rise for cheap investing in OpenAI. Unusually for such a pitch they have a pretty fantastic track record so far.

For reference, there are roughly 20mm office jobs in USA alone. Chat is currently 65% or so of all chatbot usage. The US is < 1/6 of oAi’s customer base. 10mm people currently pay for chat. OpenAI projects chat to be about 1/3 of income with no innovations beyond Agentic tool calling.

To wit: in 2029 will we be somewhere in the following band of scenarios:

Low Growth in Customers but increased model value: Will 10mm people pay $3.6k a year for chat ($300/month) worldwide in 2029, and API and Agent use each cover a similar amount of usage?

High Growth in Customers with moderate increased model value: Will 100mm people pay $360 a year for o5, which is basically o4 high but super fast and tool-connected to everything?

Ending somewhere in this band seems likely to me, not crazy. The reasons to fall out of this band are: they get beat hard and lose their research edge thoroughly to Google and Anthropic, so badly that they cannot deliver a product that can be backed by their brand and large customer base, or an Open Weights model achieves true AGI ahead of / concurrent with OpenAi and they decide not to become an inference providing company, or the world decides they don’t want to use these tools (hah), or the world’s investors stop paying for frontier model training and everyone has to move to cashflow positive behavior.

Upshot: I’d say OpenAI will be cashflow positive or $100bn+ in CF in 2029.

[viraptor]

There's still the question of whether they will try to change the architecture before they die. Using RWKV (or something similar) would drop the costs quite a bit, but will require risky investment. On the other hand some experiment with diffusion text already, so it's slowly happening.