I'd have to see the implementation in the editor to really know if I'd want it or not, but my initial impression is that I don't think it's something I would use. I've worked on a couple of products with in-editor collaboration built in (not text editors, but, content creation tools). For the most part collaboration just wasn't something users wanted that much. The problem was that the in-editor collaboration was only really useful for things that were 100% on the web, it never caught on with the more file-centric workflows. It works in something like Google Docs because it's natural that your data is in the cloud there, but for something that lives on your filesystem it feels like it takes extra steps that most people aren't going to be willing to do (especially if they have to use an editor different from their normal one)

I guess it would be perfect for pair programming in a remote work environment.

When I use these models, I honestly can't tell much of a difference between any of the frontier ones. Admittedly I'm not sitting around benchmarking them during the hype cycles, but as a coder I have zero issues switching to whatever's cheapest. Custom harnesses or whatever are not much of a moat (honestly Claude is so buggy right now that I've been using codex and opencode just so I don't have to deal with a flickery mess that screwed up my arrow keys)

I just don't see how being the "premium" provider really works if much cheaper models are basically good enough.

You should probably be more pessimistic about Meta. Look at their last major venture, the Metaverse, which was basically embarassing. Their AI strategy is incoherent.

I just looked at ccusage for a personal project. In 5 days (doing it as a hobby) I've managed to spend $250 in API tokens on a $200 subscription. 5 days, and thats on one computer (I split time using 3 of them). If I had to pay $2000 a month -- no fricking way, not worth it.

Elon Musk just got the rules of the NASDAQ changed so he can more or less force index funds to buy his shell company and take money from people's 401k. Feels very grifty to me.

That is a very misleading summary of what happened.

Saying its going to be 1500 a month across the board is highly speculative. How many companies can even demonstrate that they're getting more than 18000 dollars a year in surplus value per employee by using this tech?

How speculative would it have been to say that it was anything more than $20/mo back in November?

Sheer volume of adoption is fairly forced though - "use it or you're fired, and tokenmaxx the hell out of it". Most the people I know outside of tech don't seem to be particularly captured by it, if they use it at all.

Yes since frontier perf is too expensive. Consider though frontier perf costs roughly 40x less per year. So you see super adoption for mega costs by the companies with the scale and budget for it, and then folks who can’t afford it that have to wait until maybe fall until they have the game changing perf we saw for opus 4.5 that spurred the enormous adoption by the major players.

I agree that there are incentives to waste tokens but this is strategic: they spend now for people to build and explore, then they keep the things that work and drop the things that don’t.

Right, because markets are always rational and nobody gets greedy and ignores the skeptics until things are out of hand.

https://en.wikipedia.org/wiki/Tulip_mania

I see little evidence that people combine all three positions together. You're making a broad generalization based on personal vibes.

I see plenty if I care to look outside my usual echo chamber. There’s lots of ‘it’s just the next token prediction’ (in 2026 still!), but there are more sophisticated arguments like ‘it can’t be creative’, ‘it doesn’t think’, ‘it’s just pattern matching’ etc. They might even be true for today’s models, but linearly extrapolating an exponential trend is a classic mistake.

Confusing a logarithmic trend with an exponential one is also a classic mistake.

accurate; your point being...?

Except inference has been getting more expensive, not less

Inference has been going down in price on a cost/intelligence basis. If you don't need the smartest model, there are plenty of good Chinese models that are dirt cheap.

Doesn't that sort-of make one of Zitron's core points?

"Chinese models are dirt cheap" isn't going to do anything good for the return the investments in OpenAI and Anthropic demand.

It supports his point that they're planning to massively overbuild compute, which was already well supported by the financials. A lot of that planned compute buildout can be walked back though, and the technology is unquestionably useful in moderation, so it's not the catastrophe he suggests, and his hyperbole is part of what makes me dislike him even if there are elements of his foundational argument I agree with.

Aren't these Chinese models also heavily subsidized at the moment ? They are running off govt money which also has a cut-off date by 2028-30.

It’s been steadily getting cheaper per token per problems solved even if you don’t define ‘unsolvable => infinity token cost’

American AI companies are charging more, that doesnt mean inference isnt getting cheaper. idk why this is so hard for people to understand.

check out DeepSeek V4 Pro .... this is where the threat vector comes from IMHO. If anything is triggering a rush to IPO imho it's seeing these cheap / free models on the horizon that are "good enough" for 80% of the core use case supporting their valuation.