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If that is the case, the $300 billion question is whether someone can create a product experience that is as good as OpenAI’s.

In my mind there are really three dimensions they can differentiate on: cost, speed, and quality. Cost is hard because they’re already losing money. Speed is hard because differentiation would require better hardware (more capex).

For many tasks, perhaps even a majority right now, quality of free models is approaching good enough.

OpenAI could create models which are unambiguously more reliable than the competition, or ones which are able to answer questions no other model can. Neither of those has happened yet afaik.



Competitors just need to wait for OpenAI to burn all their free money and dig themselves a debt hole they can’t easily climb out of, and then offer a similar experience at a price that barely breaks even or makes a tiny profit, and they win.


> three dimensions they can differentiate on: cost, speed, and quality

The fourth dimension is likely to be the most powerful of the differentiators: specificity.

Think Cursor or Lovable, but tailored for other industries.

There's a weird thing where engineers tend to be highly paid, but people who employ engineers are hesitant to spend highly on tools to make their engineers more productive. Hence all Cursor's magic only gets its base price to ~50% of Intercom's entry-level fee for a tool for people who do customer support.

LLMs applied to high-value industries outside of tech are going to be a big differentiator. And the companies that build such solutions will not have the giant costs associated with building the next foundation model, or potentially operating any models at all.




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