[tguinot]

I'm sorry but I don't understand how people say LLMs are simply "tab completion".

They allow me to do much more than that thanks to all the knowledge they contain.

For instance, yesterday I wanted to write a tool that transfers any large file that is still being appended to to multiple remote hosts, with a fast throughput.

By asking Claude for help I obtained exactly what I want in under two hours.

I'm no C/C++ expert yet I have now a functional program using libtorrent and libfuse.

By using libfuse my program creates a continuously growing list of virtual files (chunks of the big file).

A torrent is created to transfer the chunks to remote hosts.

Each chunk is added to the torrent as it appears on the file system thanks to the BEP46 mutable torrent feature in libtorrent.

On each receving host, the program rebuilds the large file by appending new chunks as soon as they are downloaded through the torrent.

Now I can transfer a 25GB file (and growing) to 15 hosts as it is being written too.

Before LLM this would have taken me at least four days as I did not know those libraries.

LLMs aren't just parrots or tab completers, they actually contain a lot of useful knowledge and they're very good at explaining it clearly.

[qwertox]

> By asking Claude for help I obtained exactly what I want in under two hours.

Did you use it in your editor or via the chat interface in the browser? Because they are two different approaches, and the one in the editor is mostly a (pretty awesome) tab completion.

When I tell an LLM to "create a script which does ..." I won't be doing this in the editor, even if copilot does have the chat interface. I'll be doing this in the browser because there I have a proper chat topic to which I can get back later, or review it.

[tguinot]

I did not use copilot or cursor. I used the Claude interface. I'm planning to setup a proper editor tool such as Cursor as I believe they got much better lately. Last time I tried was 2023 and it was kind of a pain in the butt.

[qwertox]

I tried Cursor this month but even though it is much better than copilot, it also tries to do too much. And both of them fail regularly at generating proper autocompletions, which makes Cursor a bigger annoyance because it messes up your code quite often, which copilot doesn't do. Cursor is too aggressive.

But using copilot as a better autocomplete is really helpful and well worth the subscription. Just while typing as well as giving it more precise instructions via comments.

It's like a little helper in the editor, while the ChatGPT/Claude in the browser are more like "thinking machines" which can generate really usable code.

[tguinot]

good to know, thanks

[lupire]

That's fine for your quick hack that is probably a reimplementation of an existing program you can't find.

But it's not a production quality implementation of new need.

[pizzafeelsright]

I am of the strong opinion most problems were solved 20-40 years ago and that most code written today is reimplementation using different languages.

I have shipped production code using LLMs in languages I did not study approved by seasoned SWE's is evidence that an acceleration is happening.

[tguinot]

It's a knowledge base that can explain the knowledge it returns when you ask, how is that not useful in a professional environment for production code?

I mean if you assume all devs are script kiddies who simply copy paste what they find on google (or ChatGPT without asking for explanations) then yeah it's never gonna be useful in a prod setting.

Also you're very wrong to believe every technical need or combination of libraries has already been implemented in open source before.

[rty32]

True, but hey, even if it's not production code, it may be an ad-hoc thing that never gets push to production, it may be code reviewed by C++ experts and improved to production quality. At very least, someone saved four days with it, and could use the time for something, maybe something they are expert at. Isn't that still good?

[mdavid626]

Most of the time saving time is just an illusion. When that code will needed to be changed, people will spend more than 4 days debugging and understanding it. The mental model of it was written by AI. It can make sense or not at all. You’ll figure it out after 4 days.

[tguinot]

The code is 2 files of 80 lines each and is very clear. There's no way any software developer needs 4 days to understand what it does.

Moreover Claude can explain the functions used very clearly (if you're too lazy to jump to definition in your editor)

LLMs are becoming actually useful to developers new to a language. Just as Google was 20 years ago.

[mdavid626]

People talk about completey different things. The article was about Google using LLM-s to generate code, not people making 80 lines with them at home. There is a huge difference. I don’t see any problem with the latter, but with the former there are many problems.

[znpy]

That sounds like a great idea, are you going to open source that?

[tguinot]

I think I will, I don't have time to maintain additional software right for other people now but I'm definitely planning on open sourcing it when I get time

[znpy]

Yeah i see your point.

However i think that you might open source the thing with a disclaimer of no maintenance. Whoever is willing to maintain it can just fork it and move along.

[bitcharmer]

> thanks to all the knowledge they contain

This is what's problematic with modern "AI". Most people inexperienced with it, like the parent commenter will uncritically assume these LLMs poses "knowledge". This I find the most dangerous and prevalent assumption. Most people are oblivious to the fact how bad LLMs are.

[tguinot]

I know excatly how bad the output they give is, because I ask for output that I can understand, debug and improve.

People misusing tools don't make tools useless or bad. Especially since LLMs designers never claimed the compressed information inside models is spotless or 100% accurate, or based on logical reasoning.

Any serious engineer with a modicum of knowledge about neural networks knows what can or can't be done with the output.