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ChatGPT Containers can now run bash, pip/npm install packages and download files

simonwillison.net

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Re: ChatGPT Containers can now run bash, pip/npm install packages and download files

#151

Post by abrookewood »

anonzzzies wrote: post #90
bogtog wrote: post #78

Earlier quoted context omitted.

> But now that most code is written by LLMs, it's as "hard" for the LLM to write Python as it is to write Rust/Go The LLM still benefits from the abstraction provided by Python (fewer tokens and less cognitive load). I could see a pipeline working where one model writes in Python or so, then another model is tasked to compile it into a more performant language

It's very good (in our experience, YMMV of course) when/llm write prototype with python and then port automatically 1-1 to Rust for perf. We write prototypes in JS and Python and then it gets auto ported to Rust and we have been doing this for about 1 year for all our projects where it makes sense; in the past months it has been incredibly good with claude code; it is absolutely automatic; we run it in a loop until a…

Why not get it to write it in Rust in the first place?

Re: ChatGPT Containers can now run bash, pip/npm install packages and download files

#152

Post by mjevans »

manishsharan wrote: post #143
dankwizard wrote: post #116

Earlier quoted context omitted.

Me, my team, and colleagues also in software dev are all vibe coding. It's so much faster.

If I may ask, does the code produced by LLM follow best practices or patterns? What mental model do you use to understand or comprehend your codebase? Please know that I am asking as I am curious and do not intend to be disrespectful.

Think of the LLM as a slightly lossy compression algorithm fed by various pattern classifiers that weight and bin inputs and outputs.

The user of the LLM provides a new input, which might or might not closely match the existing smudged together inputs to produce an output that's in the same general pattern as the outputs which would be expected among the training dataset.

We aren't anywhere near general intelligence yet.

Re: ChatGPT Containers can now run bash, pip/npm install packages and download files

#153

Post by 1980phipsi »

simonw wrote: post #2

Regular default ChatGPT can also now run code in Node.js, Ruby, Perl, PHP, Go, Java, Swift, Kotlin, C and C++. I'm not sure when these new features landed because they're not listed anywhere in the official ChatGPT release notes, but I checked it with a free account and it's available there as well.

I was able to install the D language compiler DMD by providing a .deb file.

https://chatgpt.com/share/69781bb5-cf90-800c-8549-c845259c33...

Re: ChatGPT Containers can now run bash, pip/npm install packages and download files

#154

Post by superfrank »

koe123 wrote: post #130
behnamoh wrote: post #5

I wonder if the era of dynamic programming languages is over. Python/JS/Ruby/etc. were good tradeoffs when developer time mattered. But now that most code is written by LLMs, it's as "hard" for the LLM to write Python as it is to write Rust/Go (assuming enough training data on the language ofc; LLMs still can't write Gleam/Janet/CommonLisp/etc.). Esp. with Go's quick compile time, I can see myself using it more and m…

> But now that most code is written by LLMs Am I in the Truman show? I don’t think AI has generated even 1% of the code that I run in prod, nor does anyone I respect. Heavily inspired by AI examples, heavily assisted by AI during research sure. Who are these devs that are seeing such great success vibecoding? Vibecoding in prod seems irresponsible at best

> Who are these devs that are seeing such great success vibecoding? Vibecoding in prod seems irresponsible at best

AI written code != vibecoding. I think anyone who believes they are the same is truly in trouble of being left behind as AI assisted development continues to take hold. There's plenty of space between "Claude build me Facebook" and "I write all my code by hand"

Re: ChatGPT Containers can now run bash, pip/npm install packages and download files

#155

Post by rednafi »

logicprog wrote: post #50
simonw wrote: post #41

Earlier quoted context omitted.

Yeah, I much prefer Go to Rust for LLM things because I find Go code easy to read and understand despite having little experience with it - Rust syntax still trips me up.

Not to mention that, in general, there's a lot more to keep in mind with Rust. I've written probably tens of thousands of lines of Rust at this point, and while I used to absolutely adore it, I've really completely fallen out of love with it, and part of it is that it's not just the syntax that's horrible to look at (which I only realized after spending some time with Go and Python), but you have to always keep in mi…

This resonates with me too. I’ve written some Rust and a lot of Go. I find Rust syntax distastefully ugly, and the sluggish compilation speed doesn’t bring me any joy.

On top of that, Go has pretty much replaced my Python usage for scripting since it’s cheap to generate code and let the compiler catch obvious issues. Iteration in Rust is a lot slower, even with LLMs.

I get fasterthanlime’s rant against Go, but none of those criticisms apply to me. I write distributed-systems code for work where Go absolutely shines. I need fast compilation, self-contained binaries, and easy concurrency support. Also, the garbage collector lets me ignore things I genuinely couldn’t care less about - stuff Rust is generally good at. So choosing Go instead of Rust was kinda easy.

Re: ChatGPT Containers can now run bash, pip/npm install packages and download files

#158

Post by shevy-java »

behnamoh wrote: post #5

I wonder if the era of dynamic programming languages is over. Python/JS/Ruby/etc. were good tradeoffs when developer time mattered. But now that most code is written by LLMs, it's as "hard" for the LLM to write Python as it is to write Rust/Go (assuming enough training data on the language ofc; LLMs still can't write Gleam/Janet/CommonLisp/etc.). Esp. with Go's quick compile time, I can see myself using it more and m…

> Python/JS/Ruby/etc. were good tradeoffs when developer time mattered.

First I don't think this is the end of those languages. I still write code in Ruby almost daily, mostly to solve smaller issues; Ruby acts as the ultimate glue that connects everything here.

Having said that, Ruby is on a path to extinction. That started way before AI though and has many different reasons; it happened to perl before and now ruby is following suit. Lack of trust in RubyCentral as our divine new ruler is one (recently), after they decided to turn against the community. Soon Ruby can be renamed into Suby, to indicate Shopify running the show now. What is interesting is that you still see articles "ruby is not dead, ruby is not dead". Just the frequency of those articles coming up is worrying - it's like someone trying to pitch last minute sales - and then the company goes bankrupt. The human mind is a strange thing.

One good advantage of e. g. Python and Ruby is that they are excellent at prototyping ideas into code. That part won't go away, even if AI infiltrates more computers.

Re: ChatGPT Containers can now run bash, pip/npm install packages and download files

#159

Post by fooker »

bdangubic wrote: post #120
fooker wrote: post #96

Earlier quoted context omitted.

For most code, this never happens in the real world. The vast majority of code is garbage, and has been for several decades.

This type of comments get downvoted the most on HN but it is absolute truth, most human-written code is “subpar” (trying to be nice and not say garbage). I have been working as a contractor for many years and code I’ve seen is just… hard to put it into words. so much discussion here on HN which critiques “vibe codes” etc implies that human would have written it better which is vast vast majority is simply not the cas…

I have worked on some of the most supposedly reliable codebases on earth (compilers) for several decades, and most of the code in compilers is pretty bad.

And most of the code the compiler is expected to compile, seen from the perspective of fixing bugs and issues with compilers, is absolutely terrible. And the day that can be rewritten or improved reliably with AI can't come fast enough.

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