Off topic, but I really like the writing style on your blog. Do you have any advice for improving my own? In an older comment[1], you mentioned the craft of sharpening an idea to a very fine, meaningful, well-written point. Are there any books, or resources you’d recommend for honing that craft? Thanks in advance.

[1] https://news.ycombinator.com/item?id=44082994

I agree with what you what you have written, which is why I would never pay a subscription to an external AI provider.

I prefer to run inference on my own HW, with a harness that I control, so I can choose myself what compromise between speed and the quality of the results is appropriate for my needs.

When I have complete control, resulting in predictable performance, I can work more efficiently, even with slower HW and with somewhat inferior models, than when I am at the mercy of an external provider.

My bad — I had Max, so more than $20. I can’t edit the comment any more. Can’t keep track of the names. I wonder when ‘pro’ started to mean ‘lowest tier’.

But your article is interesting. You think some of the degradation is because when I think I’m using Opus they’re giving me Sonnet invisibily?

I used the $60/mo subscription and I bet most developers get access to AI agents via their company, and there was no difference. They should have reduced the rate limits, or offered a new model, anything except silently reduce the quality of their flagship product to reduce cost.

The cost of switching is too low for them to be able to get away with the standard enshittification playbook. It takes all of 5 minutes to get a Codex subscription and it works almost exactly the same, down to using the same commands for most actions.

So instead of breaking shit they should have just increased their prices.

Corporate software in general is often chosen based on the value returned simply being "good enough" most of the time, because the actual product being purchased is good controls for security, compliance, etc.

A corporate purchaser is buying hundreds to thousands of Claude seats and doesn't care very much about percieved fluctuations in the model performance from release to release, they're invested in ties into their SSO and SIEM and every other internal system and have trained their employees and there's substantial cost to switching even in a rapidly moving industry.

Consumer end-users are much less loyal, by comparison.

2 weeks ago the rolling session usage plummeted to borderline unusable. I'd say I get a weekly output equivalent to 2 session windows before change.

Don't confuse the many voices of a crowd with a single person's fickle view. If you can track an individual person or organization who changes their mind 'every other week' then more power to you, but unless you're performing that longitudinal study you are simply seeing differential levels of enthusiasm.

> Stop using these dopamine brain poisoning machines, think for yourself, don't pay a billionaire for their thinking machine.

Yeah, and also stop using these things they call "computers", think for yourself, write your texts by hand, send letters to people. /s

I don't think that was the main reason for people thinking OpenAI is going to collapse here.

By far, the biggest argument was that OpenAI bet too much on compute.

Being unfocused is generally an easy fix. Just cut things that don't matter as much, which they seem to be doing.

To me it seems like they burn so much money they can do lots of things in parallel. My guess would be that e.g. codex and sora are very independently developed. After all there's a quite a hard limit on how many bodies are beneficial to a software project.

Personally its down to Altman having the cognitive capacity of a sleeping snail, the world insight of a hormonal 14 year old who's only ever read one series of manga.

Despite having literal experts at his fingertips, he still isn't able to grasp that he's talking unfilters bollocks most of the time. Not to mention is Jason level of "oath breaking"/dishonesty.

> By comparison Anthropic have been very focused.

Ah yes, very focused on crapping out every possible thing they can copy and half bake?

I agree. And I am seeing it in a lot of venues, especially political discourse. Commenting is increasingly AI driven I fear the whole thing is going to collapse and nobody will be able to rely on online commentary to make decisions. At least not without a lot of independent research, maybe that’s for the best, but it’s definitely going to change the Internet.

OpenAI will need to stop burning money eventually, but so does everyone else in the space. The longer they can do this the more squeeze it puts on their competitors.

I would call out though that I think there is one way in which this differs from the Uber situation. Theoretically at some point we should hit a place where compute costs start to come down either because we've built enough resources or because most tasks don't need the newest models and a lot of the work people are doing can be automatically sent to cheaper models that are good enough. Unless Uber's self driving program magically pops back up, Uber doesn't really have that since their biggest expense is driver wages.

I think it's a long shot, but not impossible, that if OpenAI can subsidize costs long enough that prices don't need to go too much higher to be sustainable.

This is the primary reason I won’t sign up for an annual plan.

Different plan. The old 2x has been discontinued, and the bonus is now (temporarily) available for the new $100 plan users in an effort, presumably, to entice them away from Anthropic.

It’s for Pro users only, I think the 2x is up to May 31.

They did it again to "celebrate" the release of the $100 plan.

Proof they are nerfing the model? It is stable in benchmarks: https://marginlab.ai/trackers/claude-code-historical-perform...

All this just reads like just another case of mass psychosis to me

No

So many people confuse sycophantic behavior with producing results.

How is droves of your customers leaving, whether they're foot stomping or not, healthy?

Attracting talent with huge sums of money just gets you people who optimize for money, and it's usually never a good long-term decision. I think it's what led to Google's downturn.

Are those "smart people you know" machine learning researchers?

> OpenAI has a massive advantage in human capital over Anthropic.

but if your leader is a dipshit, then its a waste.

Look You can't just throw money at the problem, you need people who are able to make the right decisions are the right time. That that requires leadership. Part of the reason why facebook fucked up VR/AR is that they have a leader who only cares about features/metrics, not user experience.

Part of the reason why twitter always lost money is because they had loads of teams all running in different directions, because Dorsey is utterly incapable of making a firm decision.

Its not money and talent, its execution.

My purely unfounded, gut reaction to Opus 4.7 being released today was "Oh, that explains the recent 4.6 performance - they were spinning up inference on 4.7."

Of course, I have no information on how they manage the deployment of their models across their infra.

I'm building a correct, safe, highly understandable, concurrent runtime & language.

Essentially Rust/Tokio if it was substantially easier than even Go - and without a need for crates and a subset of the language to achieve near Ada-level safety.

The codebase is ~100k lines of code.

Yes, let take morality out of our daily lives as much as possible... That seems like a great categorical imperative and a recipe for social success

"Not everything" - sure, but mass surveillance and autonomous killing are kind of big things to sweep under that rug no?

if you're not american you should be worried about the bit of using AI to kill people which was the other major objection by Anthropic.

(not that I think the US DoD wouldn't do that anyway, ToS or not.)

Currently GPT just works much better, and so does Gemini but it's more expensive right now. Going through Opencode stats, their claim is that Gemini is the current best model followed by GPT 5.4 on their benchmarks, but the difference is slim.

My personal experience is best with GPT but it could be the specific kind of work I use it for which is heavy on maths and cpp (and some LISP).

I’m thinking the same thing, Codex literally ruined the codebases that I experimented with it on.

OpenAI replaced its founding engineers with Meta PMs. The shift towards consumer engagement metrics and marketing is apparent.

You can believe whatever you want. I found claude unusable due to limits. Codex works very well for my use cases.

I would risk a guess that people have a wrong intuition about the long-context pricing and are complaining because of that.

Yeah, the per-token price stays the same, even with large context. But that still means that you're spending 4x more cache-read tokens in a 400k context conversation, on each turn, than you would be in a 100k context conversation.

What about your chat history? That has some value, at least for me. But what has even more value is stable releases.

Codex doesn't read Claude.md like Claude does. It's not a "one line" change to switch.

Hate that about Claude Code. I have been adding permissions for it to do everything that makes sense to add when it comes to editing files, but way too often it will generate 20-30 line bash snippets using sed to do the edits instead, and then the whole permission system breaks down. It means I have to babysit it all the time to make sure no random permission prompts pop up.

> One thing I immediately like more than Claude is that Codex seems much more transparent about what it’s thinking and what it wants to do next. I find it much easier to interrupt or jump in the middle if things are going to wrong direction.

I've finally started experimenting recently with Claude's --dangerously-skip-permissions and Codex's --dangerously-bypass-approvals-and-sandbox through external sandboxing tools. (For now just nono¹, which I really like so far, and soon via containerization or virtual machines.)

When I am using Claude or Codex without external sandboxing tools and just using the TUI, I spend a lot of time approving individual commands. When I was working that way, I found Codex's tendency to stop and ask me whether/how it should proceed extremely annoying. I found myself shouting at my monitor, "Yes, duh, go do the thing!".

But when I run these tools without having them ask me for permission for individual commands or edits, I sometimes find Claude has run away from me a little and made the wrong changes or tried to debug something in a bone-headed way that I would have redirected with an interruption if it has stopped to ask me for permissions. I think maybe Codex's tendency to stop and check in may be more valuable if you're relying on sandboxing (external or built-in) so that you can avoid individual permissions prompts.

--

1: https://nono.sh/

There is a new flag for terminal flickering issues:

> Claude Code v2.1.89: "Added CLAUDE_CODE_NO_FLICKER=1 environment variable to opt into flicker-free alt-screen rendering with virtualized scrollback"

there is an official codex plugin for claude. I just have them do adversarial reviews/implementations. etc with each other. adds a bit of time to the workflow but once you have the permissions sorted it'll just engage codex when necessary

Do this -- take your coworker's PRs that they've clearly written in Claude Code, and have Codex/GPT 5.4 review them.

Or have Codex review your own Claude Code work.

It then becomes clear just how "sloppy" CC is.

I wouldn't mind having Opus around in my back pocket to yeet out whole net new greenfield features. But I can't trust it to produce well-engineered things to my standards. Not that anybody should trust an LLM to that level, but there's matters of degree here.