alt Hacker News> I think anthropic with its enterprise strategy and google with its integration in everything have a bit of a moat.
But... Anthropic doesn't have a moat. It's clear at this point that SOTA models are not a moat, and Opus 4.6-level (or GLM 5.2) is sufficient.
Google, though... they own the entire vertical, from the semiconductors to the end-user software. They may have a moat.
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Observationally, for people that /aren't/ using models to code but to just do their white-collar job, claude.ai /is/ AI, now. The entire perspective for how to use AI is through claude skills, claude projects, claude cowork, etc. They've massively won the corp buy-in at the moment I believe.
I guess I’m thinking a lot of companies seem to be getting Claude code subscriptions. It usually takes some time and effort for an org to switch away from one solution. In the meantime a lot of workflows get more and more tied to Claude in particular.
It’s not much of a moat, but it’s more than a lot of orgs have.
obligatory correction: the semiconductor layer is still owned by TSMC and Samsung. Google sketches chip designs for them to implement - that's the lowest layer they control. I am not denying that this is impressive.
The narrative that superintelligence is imminent is partially at fault here.
There are competing definitions of what intelligence even is, and the one that I find most striking is from Francois Chollet which is that intelligence can be boiled down to skill acquisition efficiency. This type of definition makes intelligence more akin to polishing a ball than growing a watermelon.
The superintelligence doomers warn that the watermelon is going to start growing exponentially and crush everyone. But what might actually be happening is that we are not growing a watermelon but rather polishing the ball until its really smooth and shiny. There's a point where you can get it to micron levels of polish but for most tasks (white collar text domains tasks), it's smooth enough! You will be able to go to the ball store and buy a low cost made in china ball for most tasks.
The real challenge is actually branching out domains and modalities to tackle things like blue collar labor. Over time, white collar work automatable or able to be made hyperefficient by LLMs will see LLM commoditization.