It seems way, way easier to switch LLMs than it is to even change from one iPhone to another iPhone!

Granted Anthropic (and Google, maybe less OpenAI actually) do what they can to make it similar. But switching phone brands would take me a day or two of planning and I don’t even use the Apple mail app.

> A banana left out in the walkway still requires the user to go for a walk.

This is some Eric-Cantona-level gnomic mysticism. I approve.

> They do not have Claude. I use Pi and other harnesses, but it's not the same.

This is going to sound tautological but of course it's not the same, because it's different?

Participants in markets make their own choices from the available options, for their own reasons.

Another way to frame my point is this: not the same for whom? You are but one market participant, and it's at least wobbly thinking for any of us to assume that our set of needs is the archetype.

There's any number of harnesses and people have any number of preferences. Sure, overchoice of imperfect substitutes tends to entrench better-resourced, better-resourced (or better-marketed) alternatives, but it's not a slam dunk. Things come out of left field all the time.

(I mean from my own perspective, I like Pi — more than OpenCode. And the "betterness" of Claude or Codex over Pi, or their models over even Muse Glimmer or Qwen, is completely irrelevant to where I am now in terms of the needs I have. So I don't use either of them and I remain unfazed. When my needs change I will revisit, but the theoretical superiority of these products for the majority of users just isn't a factor in my decision, just like I don't care that any tool I use might not be the best for most people. You might think me insane but I'm no less a rational market participant than you.)

No this is Ned Kaspersky, from Moscow (Idaho)

Here I am saying “well, shit”, over and over again, but so quickly that not even dogs can hear it.

This is very much aligned with Steve Eisman’s take: that it’s a terrible overvaluation but for Anthropic it is now or never.

OpenAI are openly suggesting 5%, but my instinct is that this is because they think Trump is foolish enough to demand double that.

And even then, the path for investors to ever make their money back is really essentially non-existent. There’s so much “total addressable market” fantasy here.

Everything we know about Anthropic’s unit economics is still riddled with EBBT. Earnings before bad things.

I assume some of this is the escalating cost of training, indeed, and that being faster means abandoning efficiency.

But you’re right. I have often wondered why it is that such a small amount of extra compute (300MW) from SpaceX was entirely enough for them to uncap so many customers.

I think the (in-house) data centre burdens of ever-more complex models may be considerable, but I think the data centre businesses expecting to serve inference tasks are probably heading into a Chinese real estate bubble.