rudedogg

Agreed. I wish they would have thrown in a "guardrails to stop me, but mostly my competitors" so the public would think about that possibility more.

Thanks for the info, I didn’t know that about the 5hr limit

Sol is their middle model. Luna is smallest. And Astra is big, their Fable equivalent.

I think the market didn’t react like they expected and now they’re like “jk”.

And I don’t think any pacing is/was intentional. They’de release skynet if they could and the stonks went up

I don’t think so, I’ve seen it suggest I try it. I’ll double check when I get home though.

I was considering the $100 plan, but I hit the 5hr limit in an hour. So even with the $100 plan I figured I cant go non-stop on a single agent running Sol Medium

I’ve been a Claude user, switched to Codex expecting usage limits to be more loose but I can’t even get through a basic sysadmin task on the $20 plan using Sol medium before I hit the 5hr one.

I think I’m gonna move back to a Claude plan. I could barely hit the $200 limit if I went non-stop on programming tasks.

> Just tell the agent to use conventional commit messages and to keep it nice and tight.

I have this in my claude.md along with guidance on (not) writing comments but it’s still dumps multi-paragraph comments of Claude speak everywhere.

I think a lot of us are talking past eachother, but what I and I think others are complaining about is doing things well, and being minimal. LLMs don’t really do that yet, they can’t look at and simplify a codebase well, even with guidance. They always seem to add rather than subtract. And eventually it becomes an issue. I think they were actually better in this regard with like Opus 4.8, and are now getting even worse (but score better, and are more autonomous).

At home I use Codex, and it’s better as far as language goes at least.

Anyway, it’s like the logic piece necessary to do good work is still missing, and hurt by recent reinforcement fine-tuning. And it leads to massive bloat since more comments = higher scores, but walls of text and the tokens (or cognition if you’re the sad human reading them) aren’t free.

Yeah, I listen/watch some flight radar youtube and it’s insane how many issues arise from the language barrier, which could be solved by just communicating via a text channel

Doing anything right on web is 10x harder and more complex. The problem is the browser, once you use it to deliver anything you have to buy into all of it’s bullshit. CORS, XSS, headers, caching. All that just goes away (outside your backend API, if you even need one) when you ship a native app

Maybe Dario shouldn’t have tried for regulatory capture. He was constantly on the news talking about how these models are so dangerous and that we need regulation to keep China from releasing open-source models without guardrails.

> You can't do that on larger models unless you have the hardware like this person does.

Or just rent something substantial for like $4/hr on runpod or w/e to do that.

My gripe is this persons compute is wasteful and makes it harder for me to buy something with like 64gb ram to do normal work and run containers while I keep using cloud models.

Someone else calculated the break even being 10 years, it’s just dumb. And I think it’s clear there won’t be a big rug pull anymore, there are too many open models and providers now.

I agree.

It would be neat to see a matrix of compile times vs. language features, showing things like:

- Bounds checks

- UAF prevention

- exhaustive enums

- test speed

But I think even among those the subtleties would make a fair comparison impossible.

Anyway I think this is all very nuanced, and anyone proclaiming language X is the language to use in 2026 lacks the experience/knowledge to consider these trade-offs and can safely be ignored.

I keep seeing these language specific proclamations, and they are annoying and reek of inexperience to me.

I’ve had a great time doing LLM assisted coding in Zig, and it seems comparable to the generic Typescript/React I do at work.

I don’t doubt simplicity and good PL design pay dividends, but everyone’s favorite language can’t be the silver bullet in our new LLM world. Things just don’t add up, and I keep seeing it for Erlang, Gleam, Lisp, C, Rust, Go, TypeScript, Python, etc.

And to pick on Go a little bit, I don’t think it has any unique qualities that make it better for LLMs, where I think you could make that argument for other modern languages that offer new features leveraging their compilers and enforcing more correctness guarantees.

> really clever people

Sam Bankman-Fried and his League of Legend rankings would like a word

> Whatever it is, SwiftUI isn't it.

I think this opinion is heavily shared by Swift developers now, but the messaging every WWDC is always "Swift and SwiftUI is the best way to build apps for Apple Platforms", etc.. If you have to keep telling everyone what they don't believe is true, it's a sign there's a problem.

It feels like someone with a lot of organizational power is disconnected from the pulse of the community. SwiftUI is undeniably clean in a lot of ways, it presents beautifully and fits on slides well, but that matters less and less, and this all wasn't really working out even before LLMs disrupted things.

> functional programming is superior for representing state in user interfaces

It's always going to be slower than using something imperative. Trying to process the entire world's state for the sake of purity can feel elegant but it isn't free. And the complexity that gets added to make things performant is worse than just accepting that UIs are going to require you to jump around the tree and modify state.

Every time I go through the trouble of understanding the latest web technique (React, Elm, Signals (the newest solution), etc.) to deal with state management and the DOM, I end up walking away disappointed. There's nothing new in them that you can use to improve what we've been doing for ages in native GUI toolkits.

And to jump back to the original topic, yes, Cocoa was pretty decent, and SwiftUI while nice in many ways tries to Reactify native macOS development and made it worse. And it made Swift incredibly more complex and worse in hindsight.

No argument that it works, it definitely does. I just think the LLMs have a hard time with tweaks/modifications of any kind, more so than what I see even in a custom GUI toolkit I’ve built that it has zero training data on.

Asking for simple changes to SwiftUI interfaces I’ve one-shot is always a frustrating experience for me

Logically this makes sense, but in practice it doesn’t, at least in my experience with SwiftUI. The LLM isn’t any better about generating/understanding it.

While the DSL is more formal than natural language, it’s not what we’re communicating to the LLM with, so it’s advantages are washed away. And typical code is more strict/rigorous than DSLs so I think that’s why I see worse results, because a typical languages compiler “catches” more mistakes, versus a DSL that’s easy to write but has lots of implicitness.

I’ve had the same journey experimenting with levels if abstraction too. Going lower, and exposing the LLM to the “full-stack” works much better than trying to build up abstractions it can’t see into without extra steps.

I don’t want to be too much of a hater, but these types of panacea/architecture posts are usually written by people who don’t work in the field, lack pressure or constraints, and get paid to goof around in castles of the mind. I would simply skip over it and hold my comments/opinions to myself, but they tend to have an outsized influence on software engineering practices.

> He says he writes slop code and doesn’t provide a single example or prove that statement.

You can look at the bun codebase. Moving fast has its drawbacks, and bun moved very fast. It’s not what I’d call idiomatic or exemplary Zig.

I think this is what Andrew was highlighting with “beginner energy”. Not knowing you shouldn’t rewrite a toolchain and take on an entire ecosystem can be a positive. I think this is pretty common in business, where someone/something isn’t “great” but wins because they didn’t know any better and went headfirst into something experts avoided because they understand the challenges and what “doing it right” entails.

Any thoughts on the latest price fixing allegations?: https://en.sedaily.com/international/2026/06/29/samsung-sk-h...

I tried CachyOS and Niri this weekend, and was pleasantly surprised hibernate/suspend actually worked with no customizations on my Desktop.

I’ve tried like 5 other distros and usually when it goes into sleep/hibernate the monitor never wakes up so I have to force shutdown using the power button.

I’m going to install this on an older machine and see how it goes. So far it’s been great!

> You talk about Anthropic giving the government 'enough rope' and getting 'owned', which seems like a tacit acknowledgement that the government does not give a shit about whatever the surface-level justification for this ban is.

I think you’re whitewashing Dario’s abhorrent behavior, and you think I’m whitewashing the government’s.

Unfortunately there’s no law against being a piece of shit and trying to pull the ladder up behind you, lobby for locking out your competitors under the guise of safety, etc..

So I have to settle for him getting swallowed by the morons he was influencing.

And if you think his concerns over safety were genuine I have a bridge to sell you.

Not sure why you're getting downvoted, or why the narrative here is all about this being payback for the Department of Whatever-the-fuck thing.

Dario has been spouting how his models are too dangerous, thinking he was playing 3D chess and got owned from my perspective. And there's the possiblility of insider plays by the current administration w/ OpenAI or SpaceX.

But Dario was running his own propaganda machine and gave them enough rope to do this.

Maybe just focusing on building solid models and running a business was the play, not trying for regulatory capture and being anti-competitive.

> organizations are willing to tolerate paying $1500/month/engineer

One organization, that is a software company

> which seems to be roughly inline with "normal" consumption for most full-time engineers

My peers are using $20/mo plans, only a handful are using more than $100/mo in tokens. We haven’t had any limits imposed yet.

That seems way off to me.

I skimmed the article, but couldn’t spot any details on their estimates. They mention 70b+ params as being large in several places. But we’ve had several 100b+ param models that trail Sonnet.

If Google is actually getting cheaper inference than everyone else with their TPUs, this smells like trouble to me. Maybe serving LLMs at a profit is proving difficult.

Or maybe they think because their benchmarks are good they can ramp up the prices. Seems like they don’t have the market share to justify a move like that yet to me.

The “Apps” app is so bad on macOS too (seems built off of Spotlight?). I’ll type the exact app name and it’ll suggest the one on my phone, an installer in Downloads, etc..

No one dog-fooded that thing.

Zig has these modern language features too fwiw.

I think the goal was to do a massive rewrite for Anthropic (they acquired bun) and show that rewriting projects from lang -> lang with Claude can reduce security vulnerabilities to help with the hype for an IPO.

I don’t use/know Rust so I can’t comment on the quality, but there was a public security review that found issues with the new Rust code: https://x.com/SwivalAgent/status/2054468328119279923

This is an interesting experiment but I’m skeptical of any claims of success by Jarred/Anthropic due to the incentive to hype agents. There’s probably a trillion dollars at stake with the IPO. And Anthropic seems to be developing this part of their business with Mythos and the super review features.

But I’d like to see the same experiment done on a project without so much relying on the story being success.

> The Fed reports

Have you happened to purchase anything in the past 12 months, and looked at the Fed's inflation numbers?

> 1) Higher level code is easier for LLMs to review and iterate upon. The more the intent is clear from the code, the easier it is for humans and LLMs to work with.

The counter-argument, and one that matches my experience is working at a lower level is actually beneficial for LLMs since they can see the whole picture and don’t have to guess at abstractions.