If you were wondering the same thing I am - it's not about skills loss, quality, and less about money spent. It's more about frontier AI shops dogfooding their own models.
CEO's nephew showed him how good the Chinese models are?
I am only half joking, I heard something like "my son or nephew did this cool thing with $X so we'll take $this_radical_step because of it" enough times over my career.
My company took away my Claude because it’s too expensive. I feel like there is a reckoning coming. The accountants are finally realising the cost of token maxing.
That's pretty stupid. Most people who are incurring significant costs are just tokenmaxxing rather than being efficient with usage. You can get 99% of jobs and work done with Haiku/Luna in a collaberating working enviroment.
I feel like people who are later to the AI game just like to "oneshot" and sink a bunch of usage into generating garbage
There really is a skill to using it effectively. I've tried coaching some of the devs on my team. Some get it, some don't.
Our company has been tracking token usage and models used vs output (tickets, story points, PRs, deploys, etc...). A dev got chewed out, even after I warned him, because he spent over $2k in a single month almost exclusively on Opus while his actual productivity in terms of what he delivered was abysmal.
Attempting a serious but not-a-certified-whatever answer: "Points" do have meaning when properly used as a kind of moving-average tool for forecasting within a particular context.
Problems arise when people try to perma-peg them to particular tasks, or (worse) man-hours or (much worse) man-hours across teams. Even just encouraging the humans to answer in terms of hours/days taints the accuracy of the forecast by introducing a kind of bias.
there's a manifold to what "effective" means. The problem is once you get into the vibe flow, it's really difficult to eject yourself into the other realms of vscode or IDE or whatever it is you normal do because the vibing provides no anchor to what you're doing.
Even if these models are smart enough to reorient themselves, they get entirely stuck in a desert and now you're asking someone to just pull up stakes and digg them out even thought they only watched them get there and the UI provides so much speed that no human can comprehend how they got there in the first place.
It's like asking a pilot to take over in an emergency situation when they're not tasked with any of the every day requirements of the job. The orgs are relying on borrowed time of experienced professionals, and that's going to erode away and what replaces it is mostly people who understand how to navigate context but not use any of the _classic_ tools.
It's a real conundrum and won't be easily surfaced but for a decade.
Or does a "collaborating work environment" mean that everything is basically spoonfed to them? Or do you only ever use ghost suggestions?
I genuinely cannot even fathom. Just how do you even get into a state where tasks are so clear and cookie cutter? These things are abhorrent. Not only are they not useful, it's an outright form of psychological torture to try and use them. They almost fight you.
Luna doesn't even respond to steers properly! You try steering it and it immediately gets distracted and then just stops.
which is quite sad because opus 5.5 is really good. i say this as an anthropic hater. i wish I could move away to other models like 6.1 sol or deepseek or whatever, but they just all lack something. i _trust_ opus 5.5
i hope other labs catch up, especially chinese labs.
Right! it seems obvious why: Both these companies want to dogfood their own coding models and stop paying competition.
You can also read this as diminishing returns / AI isn't good enough, etc, but the simplest explanation is that they don't want to send money to Anthropic.
This, and in addition to dogfooding, incentivizing employees to be more effective with the cheaper models. A lot of problems don't need anything fancy, but it takes more brain power and engineering effort to make that work. By default humans will take the path of least resistance if it's available.
If true, it is a huge blow to Anthropic’s revenue stream. IIRC it was reported that the quarter of their revenue comes from just two clients and as the ex-Meta guy who left this July, I am convinced that Meta must be one of the two.
I assume that at shops that both employ engineers and are developing an AI product, internal usage is not about improving productivity, it is about improving the offering. Of course they want employees to use internal tools.
It may bei cost efficient, but is it wise? We use not only the big US models, but also Chinese ones. This way we can compare who makes the difference. Simplified: Knowledge comes before economic aspects.
Maybe I am slow here and everyone is using Claude with credits at max use. But isn't Claude Teams like $25/month per developer for ordinary use? What the heck of these guys doing that makes it get that phenomenally expensive for their use cases? These are presumably well capable engineers who started to use this as an aid right not just throw Fable at everything and loop to the max?
There are people out there building AI building orchestrators for orchestrators for orchestrators for agents. The author of that blog post later claimed to be spending the equivalent of $122k/month on tokens (by rotating their usage between 21 accounts).
As far as I can tell, the only thing that this level of spend has produced so far is an indie 2D RPG video game.
The cybersecuritynews.com news one simply republishes details of a story published by The Information. At least they have the decency to LINK to that Information story:
I should probably know more about Claude's TOS, but it is probably a mistake for these companies not to leverage the plausible deniability of their usage and turn it into a massive distillation resource for their own models.
You're opening yourself up to data right and privacy risks with that. My company demands that I use their enterprise account because they can claim full ownership of all produced output and have full logs of every interaction.
I think that gets legally murky, if the employee is the one who pays for the tool.
I am only half joking, I heard something like "my son or nephew did this cool thing with $X so we'll take $this_radical_step because of it" enough times over my career.
I feel like people who are later to the AI game just like to "oneshot" and sink a bunch of usage into generating garbage
Our company has been tracking token usage and models used vs output (tickets, story points, PRs, deploys, etc...). A dev got chewed out, even after I warned him, because he spent over $2k in a single month almost exclusively on Opus while his actual productivity in terms of what he delivered was abysmal.
Problems arise when people try to perma-peg them to particular tasks, or (worse) man-hours or (much worse) man-hours across teams. Even just encouraging the humans to answer in terms of hours/days taints the accuracy of the forecast by introducing a kind of bias.
Even if these models are smart enough to reorient themselves, they get entirely stuck in a desert and now you're asking someone to just pull up stakes and digg them out even thought they only watched them get there and the UI provides so much speed that no human can comprehend how they got there in the first place.
It's like asking a pilot to take over in an emergency situation when they're not tasked with any of the every day requirements of the job. The orgs are relying on borrowed time of experienced professionals, and that's going to erode away and what replaces it is mostly people who understand how to navigate context but not use any of the _classic_ tools.
It's a real conundrum and won't be easily surfaced but for a decade.
Optimally? Opus will pay for itself if you save just 10% of your time
Or does a "collaborating work environment" mean that everything is basically spoonfed to them? Or do you only ever use ghost suggestions?
I genuinely cannot even fathom. Just how do you even get into a state where tasks are so clear and cookie cutter? These things are abhorrent. Not only are they not useful, it's an outright form of psychological torture to try and use them. They almost fight you.
Luna doesn't even respond to steers properly! You try steering it and it immediately gets distracted and then just stops.
>Great Depression style collapse and all the current AI companies go bankrupt.
Oh this is just a 33 day old doomer account.
i hope other labs catch up, especially chinese labs.
You can also read this as diminishing returns / AI isn't good enough, etc, but the simplest explanation is that they don't want to send money to Anthropic.
In 2026 their revenue has gone up by a factor of more than 10x, and they no longer have just two whale customers.
I heard a rumor recently that customers spending less than $100m/year aren't even considered their "top tier" now.
I believe it
There are people out there building AI building orchestrators for orchestrators for orchestrators for agents. The author of that blog post later claimed to be spending the equivalent of $122k/month on tokens (by rotating their usage between 21 accounts).
As far as I can tell, the only thing that this level of spend has produced so far is an indie 2D RPG video game.
The cybersecuritynews.com news one simply republishes details of a story published by The Information. At least they have the decency to LINK to that Information story:
https://www.theinformation.com/articles/meta-microsoft-work-...
... and of course the Information story is behind a paywall.
$1.4B/year is not a small number, even at Meta's scale, when it's money going to a competitor
I think that gets legally murky, if the employee is the one who pays for the tool.
If my employer is putting scoreboards to see and champion who uses a tool which costs money to use, they shall pay for the tool.
Sorry, I'm not a ladder climber, yet I'm not mindless enough to bankrupt myself.
After all, they should know how to compile their software. Any automation of that process is cheating their employer.
An LLM is not too dissimilar to a Work Laptop or an IDE license.