You are simply a bit too entitled. It's not a premium product and honestly not that expensive in my opinion either (though that is going to depend on your location). You are more than able to pay for API rates.
A normal person pays $0-10 for an AI plan, maybe double that for a business. $200 is premium.
It is not a premium service, it simply is buying you more tokens. Those $200 gives you at least $400 in API cost tokens.
Don't confused price with "premium service". It was not that long ago that folks would be spending $100-200 on their cable service bundle. You are buying a subsidized product when using the plan and the more you spend the more tokens you get, has nothing to do with being a premium service.
Has anybody else noticed a pretty significant shift in sentiment when discussing Claude/Codex with other engineers since even just a few months ago? Specifically because of the secret/hidden nature of these changes. I keep getting the sense that people feel like they have no idea if they are getting the product that they originally paid for, or something much weaker, and this sentiment seems to be constantly spreadin…
I dunno, I haven’t really felt gimped in the past few months. My last issue was somewhere after the holidays when the usage suddenly felt like it cratered, but quality has been consistent.
A month ago the company I work at with over 400 engineers decided to cancel all IDE subscriptions (Visual Studio, JetBrains, Windsurf, etc.) and move everyone over to Claude Code as a "cost-saving measure" (along with firing a bunch of test engineers). There was no migration plan - the EVP of Technology just gave a demo showing 2 greenfield projects he'd built with Claude Opus over a weekend and told everyone to copy…
Pretty bad decision on his part. I've been telling other engineers within my company who felt threatened by AI that this would happen. That prices would rise and the marginal cost for changes to big codebases would start to exceed the cost of an engineer's salary. API credits are expensive, especially for huge contexts, and sometimes the model will use $200 in credits trying to solve a problem that could be fixed in…
It seems very unlikely that prices would rise in the long term. Yes, RAM and GPU prices are suddenly going up due to the demand spike and OpenAI's shenanigans, but I doubt it's going to last very long. Some combination of new capacity and reduced demand will most likely put things back on the usual course where this stuff gradually gets cheaper over time. And models are getting better, so next year you can probably get the same results for less compute. That $200 in credits becomes $150, then $100, then....
A good lesson for all - I always really liked the Picasso version: In a bustling restaurant, an excited patron recognized the famous artist Picasso dining alone. Seizing the moment, the patron approached Picasso with a simple request. With a plain napkin and a big smile, he asked the artist for a drawing. He promised payment for his troubles. Picasso, ever the creator, didn’t hesitate. From his pocket, he produced a…
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It actually matches up well with the current AI scene, except backwards. We use these model which cost ridiculous amounts of money to train, and all of that effort goes into producing the outputs we use, but we're paying something not too far above the marginal cost of inference when we use them.
It’s more that Anthropic knows that the models themselves are non-sticky, and the real moat is in the ecosystem around it. It only makes sense for them to get users to use their ecosystem, rather than other tools.
See: Claude Cowork trying to establish an entire new group of people in their ecosystem.
Has anybody else noticed a pretty significant shift in sentiment when discussing Claude/Codex with other engineers since even just a few months ago? Specifically because of the secret/hidden nature of these changes. I keep getting the sense that people feel like they have no idea if they are getting the product that they originally paid for, or something much weaker, and this sentiment seems to be constantly spreadin…
I was going to do a deep analysis on this, and then I noticed that Claude Code deleted all of my sessions before March 6.
So yeah... I'm not thrilled with that, because I had done a similar analysis in December and had plenty of logs to review.
The results I do have for the last month aren't great. If you're curious I did post the results on HN:
It actually matches up well with the current AI scene, except backwards. We use these model which cost ridiculous amounts of money to train, and all of that effort goes into producing the outputs we use, but we're paying something not too far above the marginal cost of inference when we use them.
Are we at the point where there are external constraints that cash can't solve?
can't tell if you're being facetious but yes, there's not enough cash in the world to double energy/silicon fab capacity in a year. Infrastructure takes time, hardware is hard, and you have to be willing to bet that the demand will be there 5 years from now to make an investment today.
One could always make existing infrastructure more efficient. Nothing better than post-mature optimization.
I'm currently "working" on a toy 3d Vulkan Physx thingy. It has a simple raycast vehicle and I'm trying to replace it with the PhysX5 built in one ( https://nvidia-omniverse.github.io/PhysX/physx/5.6.1/docs/Ve... ) I point it to example snippets and webdocumentation but the code it gens won't work at all, not even close Opus4.6 is a tiny bit less wrong than Codex 5.4 xhigh, but still pretty useless. So, after reading…
LLMs can really only mostly do trivial things still, they're always going to do very bad work outside of what your average web developer does day-to-day, and even those things aren't a slam dunk in many cases.
That fits with my experience. I used Claude Code to put together a pretty complex CRUD app and it worked quite well. I prompted it to write the code for the analysis worker, and it produced some quite awful code with subtle race conditions which would periodically crash the worker and hang the job.
On the plus side, I got to see first-hand how Postgres handles deadlocks and read up on how to avoid them.