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Comment by nilkn | Hacker News Reader

Their moat is their research capability. It's a combination of proprietary internal technology and models and infrastructure, people, organizational structure, and culture. As long as they maintain the best and fastest research capability, they have a durable advantage, at least for the time being. If we start to saturate all economically useful outcomes that can be reached via greater research productivity attainable to us, then this moat will start to fall apart. It could also fall apart if safety issues force a premature halt or major slowdown to further research.

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This assumes any research gains last. In practice it seems like none of the frontier companies can keep much of their "secret sauce" secret for very long.

If company X has a better model than company Y, do you use it? Well, that depends: will Y take two years to catch up? If so yeah, you buy X.

But if Y is just as good a few months later, you purchase based on other factors, because you know you can live without the brilliant research X is doing ... since you'll have it soon enough.

The problem with your logic is that the history of tech is full of “good enough” eating “best” for lunch all day long. Anthropic’s plan to be the best is increasingly looking like a terrible business plan.

How long till that "research capability" becomes just 5 people with many AI agents, and no other humans in the main research loop?

I don't know and can't answer or predict that. But that's exactly what it could become (although probably not that extreme), where the agents doing much of the internal work are proprietary, conferring a research advantage.

My point is that it is not a real moat if other players can hire people from core research teams, and get a foothold that easily. And when/if models are good enough, you don't even need many people to form a fully functioning team.

It may actually get harder to replicate with time, not easier, even if the number of people needed to run the operation goes down. As the largest labs move towards internal RSI, the most important IP for doing that will transition into their proprietary internal infrastructure and models, none of which will ever be released and which increasingly won't be fully known or understood by the humans you might hire away.

> Their moat is their research capability.

Research does not bring in revenue. Products or services do.

So far, it does, because the products and services are the general intelligence produced by the research.

... on a flat slope towards commodification

You mean, if they keep running quick enough they are save? That's like the compete opposite of a moat, in my mind at least.

That's not that big of a moat though, as we've seen with DeepSeek and even smaller teams doing edge model work.

It's very hard to measure exactly how large it is, because there aren't good pre-existing metrics for it. You can measure in time (e.g., how far behind open weight models are from the best frontier models commercially available), but it's plausible that what seems like a relatively small time advantage (months) might mask a considerable difference in internal research sophistication. What we've seen repeatedly is simply that there does seem to exist a durable advantage in research productivity, at least for now.

I’m not sure I’d call maintaining the fastest research program a “durable advantage”.

If their moat is their ability to create marginal improvements every few months by releasing new models, then that is an extremely expensive moat to maintain.

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