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This should be brought up to block the patent ngl


Hey SSX, its your cousin Niko, let’s go bowling.


What's clear is that there is a lot of hype around LLM and people who were previously valued for their IC are now in the business of shilling.


I don't have much experience with Figma but looking at their prices I'd think that for someone who isn't doing a one off designs Claude Design would be much more expensive (especially if not on subscriptions) https://www.figma.com/pricing/


Assuming you need more than Figma's free tier, they're both $20/mo for individuals and small teams.


Why misadventure?


Contrary to people here who feel the price increases, reduction of subscription limits etc are the result of the Anthropic models being more expensive to run than the API & subscription revenue they generate I have a theory that Anthropic has been in the enshittification & rent seeking phase for a while in which they will attempt to extract as much money out of existing users as possible.

Commercial inference providers serve Chinese models of comparable quality at 0.1x-0.25x. I think Anthropic realised that the game is up and they will not be able to hold the lead in quality forever so it's best to switch to value extraction whilst that lead is still somewhat there.


> Commercial inference providers serve Chinese models of comparable quality…

"Comparable" is doing some heavy lifting there. Comparable to Anthropic models in 1H'25, maybe.


Benchmarks suggests they are comparable: https://artificialanalysis.ai/?models=claude-opus-4-6-adapti...

But let's say for the sake of discussion Opus is much better - still doesn't justify the price disparity especially when considering that other models are provided by commercial inference providers and anthropics is inhouse.


Try doing real work with them, it's night and day difference especially for systems programming. The non-frontier models to a lot of benchmaxxing to look good.


> Benchmarks suggests they are comparable

The problem here is people think AI benchmarks are analogous to say, CPU performance benchmarks. They're not:

* You can't control all the variables, only one (the prompt).

* The outputs, BY DESIGN, can fluctuate wildly for no apparent reason (i.e., first run, utter failure, second run, success).

* The biggest point, once a benchmark is known, future iterations of the model will be trained on it.

Trying to objectively measure model performance is a fool's errand.


The answer has always been the same: self-regulated profession and trade unions. Instead the ever efficient software engineers have efficiently dug their own grave. The regulated professions aren't going to be affected by the AI because their members understand that preservation of job security[0], their pay and QOL is more important than automating themselves out of existence.

[0] https://www.bma.org.uk/news-and-opinion/medical-degree-appre...


Which regulated professions? Trade unions still require work for their members to do. If there's a recession and say a construction slump, it doesn't matter how high or low the union's regulations are for their members, if there's no work, there's no work.

Medical doctors are a special case, but eg iron workers theres the official list people get called up from, but you're not getting called up from that list if there's no work. You get work through knowing the right person aka networking. Which is where software engineers find themselves today.


> Which regulated professions?

All other engineering (civil, chemistry, mechanical, electrical, ...) and semi-engineering (architecture) disciplines.


Yes, this is so true. But we never thought about that but instead thought about how smart and better and productive we are over other people in similar position.

Also you forgot the link?


I'm not convinced, Kimi 2.5, GLM 5.1, Minimax M2.7 are all fraction of the price and still make money on inference.


I wonder what effect AI had on online education - course signups, new resources being added etc.

I’ve recently started csprimer and whilst mentally stimulating I wonder if I’m not completely wasting my time.


That’s a good analogy but I think we’ve already went from 0 to 10 rungs over the last couple of years. If we assume that the models or harnesses will improve more and more rungs will be removed. Vast majority of programmers aren’t doing novel, groundbreaking work.


I think this was an unpopular opinion mainly because it's scary, rather than there being an obvious reason to think otherwise.


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