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 spreading. Like when I hear Anthropic mentioned in the past few weeks, it's almost always in some negative context.
- Banning OpenClaw users (within their rights, of course, but bad optics)
- Banning 3rd party harnesses in general (ditto)
(claude -p still works on the sub but I get the feeling like if I actually use it, I'll get my Anthropic acct. nuked. Would be great to get some clarity on this. If I invoke it from my Telegram bot, is that an unauthorized 3rd party harness?)
- Lowering reasoning effort (and then showing up here saying "we'll try to make sure the most valuable customers get the non-gimped experience" (paraphrasing slightly xD))
- Massively reduced usage (apparently a bug?) The other day I got 21x more usage spend on the same task for Claude vs Codex.
- Noticed a very sharp drop in response length in the Claude app. Asked Claude about it and it mentioned several things in the system prompt related to reduced reasoning effort, keeping responses as brief as possible, etc.
It's all circumstantial but everything points towards "desperately trying to cut costs".
I love Claude and I won't be switching any time soon (though with the usage limits I'm increasingly using Codex for coding), but it's getting hard to recommend it to friends lately. I told a friend "it was the best option, until about two weeks ago..." Now it's up in the air.
> It's all circumstantial but everything points towards "desperately trying to cut costs".
I have been wondering if it's more geared at reducing resource usage, given that at the moment there's a known constraint on AI datacenter expansion capability. Perhaps they are struggling to meet demand?
> (claude -p still works on the sub but I get the feeling like if I actually use it, I'll get my Anthropic acct. nuked. Would be great to get some clarity on this. If I invoke it from my Telegram bot, is that an unauthorized 3rd party harness?)
100% this, I’ve posted the same sentiment here on HN. I hate the chilling effect of the bans and the lack of clarity on what is and is not allowed.
There’s the argument that Anthropic has built Claude Code to use the models efficiently, which the subscription pricing is based on.
Maybe there’s some truth to that, but then why haven’t OpenAI made the same move? I believe the main reason is platform control. Anthropic can’t survive as a pipeline for tokens, they need to build and control a platform, which means aggressively locking out everybody else building a platform.
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 they'd built with Claude Opus over a weekend and told everyone to copy how he worked. A week later the EVP had to send out an email telling people to stop using Opus because they were burning through too many tokens.
Claude seems to be getting nerfed every week since we've switched. I wonder how our EVP is feeling now.
Hopefully that EVP feels embarrassed that a big bet was made that not only didn't pay off but left the company in a worse position. Some schadenfreude may be all you can expect, since this is an executive.
Yeah I’ve seen this too. It’s difficult for me to tell if the complaints are due to a legitimate undisclosed nerf of Claude, or whether it’s just the initial awe of Opus 4.6 fading and people increasingly noticing its mistakes.
I think there's a much more nefarious reason that you're missing.
It's pretty clear that OpenAI has consistently used bots on social networks to peddle their products. This could just be the next iteration, mass spreading lies about Anthropic to get people to flock back to their own products.
That would explain why a lot of users in the comments of those posts are claiming that they don't see any changes to limits.
The trouble with that argument, though, is that it works the other way as well: how do I, a random internet citizen, know that you're not doing the same thing for Anthropic with this comment?
(FWIW I have definitely noticed a cognitive decline with Claude / Opus 4.6 over the past month and a half or so, and unless I'm secretly working for them in my sleep, I'm definitely not an Anthropic employee.)
Oh it's pretty clear to me that Anthropic employs the same tactics and uses bots on socials to push its products too. On Reddit a couple of months ago it was simply unbearable with all the "Claude Opus is going to take all the jobs".
You definitely shouldn't trust me, as we're way beyond the point where you can trust ANYTHING on the internet that has a timestamp later than 2021 or so (and even then, of course people were already lying).
Personally I use Claude models through Bedrock because I work for Amazon, and I haven't noticed any decline. Instead it's always been pretty shit, and what people describe now as the model getting lost of infinite loops of talking to itself happened since the very start for me.
Judging from the number of GitHub issues on Anthropic, shamelessly being dismissed as "fixed", I doubt openai needs the bots to tarnish that competitor.
I'm on the enterprise team plan so a decent amount of usage.
In March I could use Opus all day and it was getting great results.
Since the last week of March and into April, I've had sessions where I maxed out session usage under 2 hours and it got stuck in overthinking loops, multiple turns of realising the same thing, dozens of paragraphs of "But wait, actually I need to do x" with slight variations of the same realisation.
This is not the 'thinking effort' setting in claude code, I noticed this happening across multiple sessions with the same thinking effort settings, there was clearly some underlying change that was not published that made the model get stuck in thinking loops more for longer and more often without any escape hatch to stop and prompt the user for additional steering if it gets stuck.
I’ve seen the point raised elsewhere that this could be the double usage promo that was available from the 13th of March to the 28th. ie. people getting used to the promo then feeling impacted when it finished.
Although it seems that enterprise wasn’t included, so maybe not in your case.
its sounds like, tinfoil hat, they reduced the quant size of their model and tried to mask the change with the promo. your theory only addresses the spend not the reduced realiability
Whenever I see Opus say “but wait, …”—which is all the time—I get a little bit closer toward throwing my computer out the window. Sometimes I just collapse the thinking section, cross my fingers, and wait for the answer. It’s too frustrating watching the thinking process.
The enshittification meme has been taken too seriously to the point where it is shoehorned into every single place possible.
It is not in the interests for Anthropic to screw its customer base. Running a frontier lab comes with tradeoffs between training, inference and other areas.
This shows a lack of understanding of how markets work. Investors make money when the valuation of the company increases. The valuation of the company is the best prediction of future profit risk adjusted.
How would anthropic increase future profits without satisfying customers?
I certainly noticed a significant drop in reasoning power at some point after I subscribed to Claude. Since then I've applied all sorts of fixes that range from disabling adaptive thinking to maxing out thinking tokens to patching system prompts with an ad-hoc shell script from a gist. Even after all this, Opus will still sometimes go round and round in illogical circles, self-correcting constantly with the telltale "no wait" and undoing everything until it ends up right where it started with nothing to show for it after 100k tokens spent.
Whether it's due to bugs or actual malice, it's not a good look. I genuinely can't tell if it's buggy, if it's been intentionally degraded, if it's placebo or if it's all just an elaborate OpenAI psyop.
On OpenRouter token consumption is up 5x since November 2025. If this is indicative of the industries growth then I can't fathom how we will not hit resource constraints.
Phase 3: $20,000/mo limited release model "too dangerous" to use
Phase 4: Accelerated layoffs / two person teams. Rehiring of certain personnel at lower costs.
Phase 5: "Our new model can decompile and rewrite any commercial software. We just wrote a new kernel after looking at Linux (bye, bye GPL!) We also decompiled the latest Zelda game, ported the engine to Rust, and made a new game with it. Source code has no value. Even compiled and obfuscated code is a breeze to clone."
Phase 6: $100k/mo model that replicates entire engineering teams, only large companies can afford it. Ordinary users can't buy. More layoffs.
Phase N: People can't afford computing anymore. Everything is thin clients and rented. It's become like the private railroad industry. End of the PC era. Like kids growing up on smartphones, there's nothing to tinker with anymore. And certainly no gradient for entrepreneurship for once-skilled labor capital.
Anothropic used to be cool before they started gating access. Limiting Claw/OpenCode was strike one. Mythos is strike two.
Y'all should have started hating on their ethics when they started complaining about being distilled. For training they conducted on materials they did not own.
We need open weights companies now more than ever. Too bad China seems to be giving up on the idea.
Stop thinking billion dollar publicly traded companies are "cool" just because they make widget you like.
You will be backstabbed
You will be squeezed for all they can.
And you will be betrayed.
> Phase N: People can't afford computing anymore. Everything is thin clients and rented. It's become like the private railroad industry. End of the PC era. Like kids growing up on smartphones, there's nothing to tinker with anymore. And certainly no gradient for entrepreneurship for once-skilled labor capital.
Thankfully none of them actually makes money and just runs on investment so there is a good chance bubble will drop and the price of PC equipment will... continue to rise as US gives up Taiwan to China
What I want to know is how did they make the only LLM that doesn't sound cringe?
I think it has something to do with mode collapse (although Claude certainly has its own "tells"), but I'm not sure.
It sounds trivial but even for Agentic, I found the writing style to be really important. When you give Claude a persona, it sounds like the thing. When you give GPT a persona, it sounds like GPT half-assedly pretending to be the thing.
---
Some other interesting points about Anthropic's models. I don't know if any of these relate to my LLM style question, but seems worth mentioning:
Claude models also use way less tokens for the same task (on ArtificialAnalysis, they are a clear outlier on this metric).
And there's a much stronger common sense, subjectively. (Not sure if we have a good way to actually measure that, though.) It takes context and common sense into account, to a much greater degree.
(Which ties in with their constitution. Understanding why things are wrong at a deeper level, rather than just surface level pattern matching.)
Opus is great but it should be bigger. You notice the difference between Sonnet and Opus, but with heavy use you notice Opus's limitations, too.
Why would any company release open weights once the investment money stops ?
Releasing open weights have been basically a PR move, the moment those companies need to actually make money they will cut it out as that reduces their client base.
They DO NOT want you to run AI. They want you to pay them to do it
z.ai did go public on the HK exchange. They are under pressures similar to other public companies.
I know that China models are increasingly being trained and run using Huawei chips instead of Nvidia. I know China has a surplus of electricity from renewables (wind, solar, hydro).
It all boils down to a brilliant but extremely expensive technology. Both to build and to run.
We've been sold a product with heavy subsidy. The idea (from Sam) scale out and see what happens.
Those who care to read between the lines can see what's happening. A perfect storm of demand that attract VCs who can't understand they are the real customers. Once they understand that it will be too late.
Regarding open weight models: eventually we will, as humanity, benefit from the astronomical capital poured into developing a technology ahead of its time. In a few years this and even more will run on edge.
Written by open source developers, likely former openai and anthropic employees who got so much cash in the bank they don't need to worry about renting their knowledge.
> We need open weights companies now more than ever.
If you're objective it to democratize AI, sure. But for those fed up with it and the devastating effects it's having on students, for example, can opt to actively avoid paying for products with AI (I say this as someone who uses it every day, guilty). At some point large companies will see that they're bleeding money for something that most people don't seem to want, and cancel those $100k/mo deals. I've already experienced one AI-developer-turned company crash and burn.
Personally, I don't think this LLM-based AI generation will have any significant positive impacts. Time, energy (CO2) and money would have been far better spent elsewhere.
> End of the PC era, there's nothing to tinker with anymore. And certainly no gradient for entrepreneurship for once-skilled labor capital.
This one seems too far fetched. Training models is widespread. There will always be open weight models in some form, and if we assume there will be some advancements in architecture, I bet you could also run them on much leaner devices. Even today you can run models on Raspberry Pis. I don't see a reason this will stop being a thing, there will be plenty of ways to tinker.
However, keep in mind the masses don't care about tinkering and never have. People want a ChatGPT experience, not a pytorch experience. In essence this is true for all tech products, not just AI.
New theory of HN: every post on LLMs will attract the "what is wrong with AI? I don't get it [even though I've posted to HN every day for weeks/months on LLM/AI topics]. Please enlighten me" types
Several thoughts went through my head before I realized what's wrong:
1. I guess longer caching means more stale data, which is why it's a downgrade?
2. Maybe this isn't the TTL I thought it was?
3. Maybe this isn't the cache I thought?
Then I clicked on the link and realized I had been mislead my the title.
It's also routinely failing the car wash question across all models now, which wasn't the case a month ago. :-/
Seeing some things about how the effort selector isn't working as intended necessarily and the model is regressing in other ways: over-emphasizing how "difficult" a problem is to solve and choosing to avoid it because of the "time" it would take, but quoted in human effort, or suggesting the "easier" path forward even if it's a hack or kludge-filled solution.
Awesome, I didn't know about the car wash question.
Totally true, also tokens seem to burn through much faster. More parallelism could explain some of it but where I could work on 3-5 projects at once on the max plan a month ago, I can't even get one to completion now on the same Opus model before the 5h session locks me up..
Obviously it cannot. But if you give the AI enough hints, clear spec, clear documentation and remove all distracting information, it can solve most problems.
I have also switched from claude to codex a few weeks ago. After deciding to let agents only do focused work I needed less context, and the work was easier to review. Then I realized codex can deliver the same quality, and it's paid through my subscription instead of per token.
I made this switch months ago, ChatGPT 5.4 being a smarter model, but I’ve had subjective feelings of degradation even on 5.4 lately. There’s a lot of growth in usage right now so not sure what kind of optimizations their doing at both companies
I would switch to Codex, but Altman is such a naked sociopath and OpenAI so devoid of ethical business practices that I can't in good conscience. I'm not under any illusion that Anthropic is ethical, but it is so far a step up from OpenAI.
I'm with you on the ethical part, but everything is a spectrum. All the AI leadership are some shade of evil. There's no way the product would be effective if they weren't. I don't like that Sam Altman is a lunatic, but frankly they all are. I also recognize that these are massive companies filled with non shitty engineers who are actually responsible for a lot of the magic. Conflating one charlatan with the rest of it is a tragedy of nuance.
Out of the loop here, what did Sam Altman do that is considered a sociopath and what did OpenAI do that is uniquely unethical that one should avoid it?
This keeps popping up in every thread and I want to separate virtue signalling and genuine fear of OpenAI.
There's not one thing that stands out, but he abandoned the entire core principles of OpenAI (took a 180), constantly lies to people and doesn't plan to stop.
Just give us the option to get the quality back, Anthropic. I get that even a $200 subscription is not possible eventually, but give us the option to sub the $1000 tier or tell us to use the API tier, but give us some consistency.
the parallel druggie are the AI companies who want to quit burning cash but tealize their users are all addicted to 40k GPUs that cost $100s dollars a month to use and theres no way to train a SOTA model better and guarantee better efficiency; so you promo double tokens as a cover for a QUANT downgrade while publishing a reskinned "upgrade" as super killer AI hoping some B2B will take a hit of the crack pipe.
This coincides with Anthropic's peak-hour announcement (March 26th). Could the throttling be partly a response to infrastructure load that was itself inflated by the TTL regression?
It would be too fucking funny if this were the case. They're vibe coding their infrastructure and they vibe coded their response to the increased load.
You'd think they would have dashboards for all of this stuff, to easily notice any change in metrics and be able to track down which release was responsible for it.
It's absolutely ridiculous how stupid Claude is now. I sometimes notice it and last year too but it feels like it's just last year before December model.
I also noticed this, just resuming something eats up your entire session. The past two weeks also felt like a substantial downgrade and made me regret renewing my subscription, it sucks because I wish I kept my Codex subscription instead and renewed that.
This is the same shit openAI used to do last year, quietly downgrading their offerings while hyping the next big thing. I thought Anthropic were different but it seems they're playing the exact same long con with Mythos.
They can't really revolutionize AI again so they make the product worse and worse and then offer you a "better" one
Since I (until Anthropic decided to remove access for subs) used Anthropic models extensively with pi I explored the two caching options and the much higher cost of 1h caches is almost never a good tradeoff.
Since the caching really primarily is something they can be judged at scale from across many users I can only assume that Anthropic looked at their infra load and impact and made a very intentional change.
If youre reading this claude, people are willing to pay extra if you want to make more money, just please stop doing this undermining, it devreases the trust of your platform to something that cannot be relied on
Caching LLM is not like caching normal content; the longer it is the more beneficial it is and it only stops being worth when user stops current session.
So you'd need some adaptive algorithm to decide when to keep caching and when to purge it whole, possibly on client side, but if you give client the control, people will make it use most cache possible just to chase diminishing returns. So fine grained control here isn't all that easy; other possible option is just to have cache size per account and then intelligently purge it instead of relying just on TTL
Am I the only one who sees striking parallels between being a Claude Code customer and Cuckoldry (as in biology)?
I mean, you are investing a lot (infrastructure and capital) into something that is essentially not yours. You claim credit for the offspring (the solution) simply because it resides in your workspace. You accept foreign code to make your project appear more successful and populated than you could manage alone. Your over-reliance on a surrogate for the heavy lifting leads to the loss of your own survival skills (coding and debugging). Last but not least, you handle the grunt work of territory defense (clients and environments) while the AI performs the actual act of creation (Displaced Agency).
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 spreading. Like when I hear Anthropic mentioned in the past few weeks, it's almost always in some negative context.
- Banning OpenClaw users (within their rights, of course, but bad optics)
- Banning 3rd party harnesses in general (ditto)
(claude -p still works on the sub but I get the feeling like if I actually use it, I'll get my Anthropic acct. nuked. Would be great to get some clarity on this. If I invoke it from my Telegram bot, is that an unauthorized 3rd party harness?)
- Lowering reasoning effort (and then showing up here saying "we'll try to make sure the most valuable customers get the non-gimped experience" (paraphrasing slightly xD))
- Massively reduced usage (apparently a bug?) The other day I got 21x more usage spend on the same task for Claude vs Codex.
- Noticed a very sharp drop in response length in the Claude app. Asked Claude about it and it mentioned several things in the system prompt related to reduced reasoning effort, keeping responses as brief as possible, etc.
It's all circumstantial but everything points towards "desperately trying to cut costs".
I love Claude and I won't be switching any time soon (though with the usage limits I'm increasingly using Codex for coding), but it's getting hard to recommend it to friends lately. I told a friend "it was the best option, until about two weeks ago..." Now it's up in the air.
I have been wondering if it's more geared at reducing resource usage, given that at the moment there's a known constraint on AI datacenter expansion capability. Perhaps they are struggling to meet demand?
100% this, I’ve posted the same sentiment here on HN. I hate the chilling effect of the bans and the lack of clarity on what is and is not allowed.
Maybe there’s some truth to that, but then why haven’t OpenAI made the same move? I believe the main reason is platform control. Anthropic can’t survive as a pipeline for tokens, they need to build and control a platform, which means aggressively locking out everybody else building a platform.
it's a bug only if they get a harsh public response, otherwise it becomes a feature
I've used it with a sub a lot. Concurrency of 40 writing descriptions of thousands of images, running for hours on sonnet.
I have a lot of complaints. I've cancelled my $200 subscription and when it runs out in a few days I'll have to find something else.
But claude -p is fine.
... Or it was 2 week ago. Who knows if they've silently throttled it by now?
Claude seems to be getting nerfed every week since we've switched. I wonder how our EVP is feeling now.
It's pretty clear that OpenAI has consistently used bots on social networks to peddle their products. This could just be the next iteration, mass spreading lies about Anthropic to get people to flock back to their own products.
That would explain why a lot of users in the comments of those posts are claiming that they don't see any changes to limits.
(FWIW I have definitely noticed a cognitive decline with Claude / Opus 4.6 over the past month and a half or so, and unless I'm secretly working for them in my sleep, I'm definitely not an Anthropic employee.)
You definitely shouldn't trust me, as we're way beyond the point where you can trust ANYTHING on the internet that has a timestamp later than 2021 or so (and even then, of course people were already lying).
Personally I use Claude models through Bedrock because I work for Amazon, and I haven't noticed any decline. Instead it's always been pretty shit, and what people describe now as the model getting lost of infinite loops of talking to itself happened since the very start for me.
I'm on the enterprise team plan so a decent amount of usage.
In March I could use Opus all day and it was getting great results.
Since the last week of March and into April, I've had sessions where I maxed out session usage under 2 hours and it got stuck in overthinking loops, multiple turns of realising the same thing, dozens of paragraphs of "But wait, actually I need to do x" with slight variations of the same realisation.
This is not the 'thinking effort' setting in claude code, I noticed this happening across multiple sessions with the same thinking effort settings, there was clearly some underlying change that was not published that made the model get stuck in thinking loops more for longer and more often without any escape hatch to stop and prompt the user for additional steering if it gets stuck.
Although it seems that enterprise wasn’t included, so maybe not in your case.
https://support.claude.com/en/articles/14063676-claude-march...
It is not in the interests for Anthropic to screw its customer base. Running a frontier lab comes with tradeoffs between training, inference and other areas.
How would anthropic increase future profits without satisfying customers?
Whether it's due to bugs or actual malice, it's not a good look. I genuinely can't tell if it's buggy, if it's been intentionally degraded, if it's placebo or if it's all just an elaborate OpenAI psyop.
https://news.ycombinator.com/item?id=47664442
Configuration and environment variables seem to have improved things somewhat but it still seems to be hit or miss.
Phase 1: $200/mo prosumer engineer tool
Phase 2: AI layoffs / "it's just AI washing"
Phase 3: $20,000/mo limited release model "too dangerous" to use
Phase 4: Accelerated layoffs / two person teams. Rehiring of certain personnel at lower costs.
Phase 5: "Our new model can decompile and rewrite any commercial software. We just wrote a new kernel after looking at Linux (bye, bye GPL!) We also decompiled the latest Zelda game, ported the engine to Rust, and made a new game with it. Source code has no value. Even compiled and obfuscated code is a breeze to clone."
Phase 6: $100k/mo model that replicates entire engineering teams, only large companies can afford it. Ordinary users can't buy. More layoffs.
Phase N: People can't afford computing anymore. Everything is thin clients and rented. It's become like the private railroad industry. End of the PC era. Like kids growing up on smartphones, there's nothing to tinker with anymore. And certainly no gradient for entrepreneurship for once-skilled labor capital.
Anothropic used to be cool before they started gating access. Limiting Claw/OpenCode was strike one. Mythos is strike two.
Y'all should have started hating on their ethics when they started complaining about being distilled. For training they conducted on materials they did not own.
We need open weights companies now more than ever. Too bad China seems to be giving up on the idea.
"You wouldn't distill an Opus."
You will be backstabbed
You will be squeezed for all they can.
And you will be betrayed.
> Phase N: People can't afford computing anymore. Everything is thin clients and rented. It's become like the private railroad industry. End of the PC era. Like kids growing up on smartphones, there's nothing to tinker with anymore. And certainly no gradient for entrepreneurship for once-skilled labor capital.
Thankfully none of them actually makes money and just runs on investment so there is a good chance bubble will drop and the price of PC equipment will... continue to rise as US gives up Taiwan to China
I think it has something to do with mode collapse (although Claude certainly has its own "tells"), but I'm not sure.
It sounds trivial but even for Agentic, I found the writing style to be really important. When you give Claude a persona, it sounds like the thing. When you give GPT a persona, it sounds like GPT half-assedly pretending to be the thing.
---
Some other interesting points about Anthropic's models. I don't know if any of these relate to my LLM style question, but seems worth mentioning:
Claude models also use way less tokens for the same task (on ArtificialAnalysis, they are a clear outlier on this metric).
And there's a much stronger common sense, subjectively. (Not sure if we have a good way to actually measure that, though.) It takes context and common sense into account, to a much greater degree.
(Which ties in with their constitution. Understanding why things are wrong at a deeper level, rather than just surface level pattern matching.)
Opus is great but it should be bigger. You notice the difference between Sonnet and Opus, but with heavy use you notice Opus's limitations, too.
I've been using GLM for over 6 months and pretty happy.
Releasing open weights have been basically a PR move, the moment those companies need to actually make money they will cut it out as that reduces their client base.
They DO NOT want you to run AI. They want you to pay them to do it
z.ai did go public on the HK exchange. They are under pressures similar to other public companies.
I know that China models are increasingly being trained and run using Huawei chips instead of Nvidia. I know China has a surplus of electricity from renewables (wind, solar, hydro).
So, it makes a lot of sense to get people a "demo" and claim the paid product is better.
i think a lot of people have no idea how capable local models are atm.
It all boils down to a brilliant but extremely expensive technology. Both to build and to run.
We've been sold a product with heavy subsidy. The idea (from Sam) scale out and see what happens.
Those who care to read between the lines can see what's happening. A perfect storm of demand that attract VCs who can't understand they are the real customers. Once they understand that it will be too late.
Regarding open weight models: eventually we will, as humanity, benefit from the astronomical capital poured into developing a technology ahead of its time. In a few years this and even more will run on edge.
Written by open source developers, likely former openai and anthropic employees who got so much cash in the bank they don't need to worry about renting their knowledge.
If you're objective it to democratize AI, sure. But for those fed up with it and the devastating effects it's having on students, for example, can opt to actively avoid paying for products with AI (I say this as someone who uses it every day, guilty). At some point large companies will see that they're bleeding money for something that most people don't seem to want, and cancel those $100k/mo deals. I've already experienced one AI-developer-turned company crash and burn.
Personally, I don't think this LLM-based AI generation will have any significant positive impacts. Time, energy (CO2) and money would have been far better spent elsewhere.
This one seems too far fetched. Training models is widespread. There will always be open weight models in some form, and if we assume there will be some advancements in architecture, I bet you could also run them on much leaner devices. Even today you can run models on Raspberry Pis. I don't see a reason this will stop being a thing, there will be plenty of ways to tinker.
However, keep in mind the masses don't care about tinkering and never have. People want a ChatGPT experience, not a pytorch experience. In essence this is true for all tech products, not just AI.
The SI symbol for minutes is "min", not "M".
A compromise would be to use the OP notation "m".
I'm aware of that, and thought that "downgraded" was the wrong word to use when going from 1h to 5 months.
1. I guess longer caching means more stale data, which is why it's a downgrade? 2. Maybe this isn't the TTL I thought it was? 3. Maybe this isn't the cache I thought?
Then I clicked on the link and realized I had been mislead my the title.
Seeing some things about how the effort selector isn't working as intended necessarily and the model is regressing in other ways: over-emphasizing how "difficult" a problem is to solve and choosing to avoid it because of the "time" it would take, but quoted in human effort, or suggesting the "easier" path forward even if it's a hack or kludge-filled solution.
Totally true, also tokens seem to burn through much faster. More parallelism could explain some of it but where I could work on 3-5 projects at once on the max plan a month ago, I can't even get one to completion now on the same Opus model before the 5h session locks me up..
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 all the success stories here and everywhere, I'm wondering if I'm holding it wrong or if it just can't solve everything yet.
Obviously it cannot. But if you give the AI enough hints, clear spec, clear documentation and remove all distracting information, it can solve most problems.
This keeps popping up in every thread and I want to separate virtue signalling and genuine fear of OpenAI.
https://www.newyorker.com/magazine/2026/04/13/sam-altman-may...
You know, you can just google his name yourself, don't you?
</tinfoil>
They can't really revolutionize AI again so they make the product worse and worse and then offer you a "better" one
Since the caching really primarily is something they can be judged at scale from across many users I can only assume that Anthropic looked at their infra load and impact and made a very intentional change.
Why the FUD?
I notice some interesting public opinion weather change since Anthropic passed OpenAI wrt revenue
So you'd need some adaptive algorithm to decide when to keep caching and when to purge it whole, possibly on client side, but if you give client the control, people will make it use most cache possible just to chase diminishing returns. So fine grained control here isn't all that easy; other possible option is just to have cache size per account and then intelligently purge it instead of relying just on TTL
the hardware VM model is almost identical. Each session can go anywhere to start but a live session cant just be routed anywhere without penalty.
I mean, you are investing a lot (infrastructure and capital) into something that is essentially not yours. You claim credit for the offspring (the solution) simply because it resides in your workspace. You accept foreign code to make your project appear more successful and populated than you could manage alone. Your over-reliance on a surrogate for the heavy lifting leads to the loss of your own survival skills (coding and debugging). Last but not least, you handle the grunt work of territory defense (clients and environments) while the AI performs the actual act of creation (Displaced Agency).