Let's face it the only reason you're saying "coding is a practical use case" is because you yourself don't code, and don't understand it.

Usually only the last statement is true.

I think there is quite a bit more subtlety than that.

Yes, just asking an LLM, even the latest versions, to write some code goes from “wow, that’s pretty good” to “eh, not great but ok for something I’m going to use once and then not care about” to “fucking terrible” as the size goes up. And all the agents in the world don’t really make it better.

But… there are a few use cases that I have found interesting.

1. Project management, plannning, and learning new languages/domains when using a core prompt as described at: https://www.codingwithjesse.com/blog/coding-with-llms-can-still-be-fun/

I like to add:

- Do not offer to write code unless the user specifically requests it. You are a teacher and reviewer, not a developer 
- Include checks for idiomatic use of language features when reviewing 
- The user has a strong background in C, C++, and Python. Make analogies to those languages when reviewing code in other languages

as well when I’m using it to help me learn a new language.

1. Reviews of solo projects. I like working with someone else to review my code and plans at work, particularly when I’m working in a domain or language that I don’t have experience in. But for solo projects I don’t have someone to give me reviews, so asking a coding LLM “Review this project, looking for architectural design issue, idiomatic language use, and completeness. Do not offer to fix anything, just create an issue list.” is really helpful. I can take the list, ignore anything I disagree with, and use it for a polishing round.

Just ask those people to read engrish, they'll stand a chance of understanding the issue. It's put together with clues of how it works, and can copypaste pieces, but without the knowledge to string it all together cohesively. Maybe not the best example, but coding is a language like English is a language, and we take a lot of our knowledge for granted when it comes to our intimate relationship with language.

If you want bug ridden code with security issues which is not extensible and which no-one understands, then sure, it's a practical use case.

This assumes you never review it, meaning it’s at best an argument against vibe coding. It’s not an argument against using LLMs for coding in general.

Additionally, I’ve been writing software for a living for almost 30 years, and I could say the exact same thing about a lot of human generated code I’ve reviewed during that time. I don’t even know how often I’ve explained basic stuff like “security goes in the backend, not in the frontend” to humans.

Let's face it the only reason you're saying "coding is a practical use case" is because you yourself don't code, and don't understand it.

I certainly do code and if I don’t understand what the LLM outputs it doesn’t go in the project.

I can't see another reason why would assume the problems experienced in other domains somehow don't apply to coding.

I’m a software engineer, I can’t judge LLMs in most other domains. I also don’t think there are no problems. A tool doesn’t have to be 100% problem free to be useful as long as you recognize the limitations.

So you're going to have to pick your way through every single line it generates in order to have the same confidence you would have if you wrote it

I don’t see a problem with this. The post even mentions pulling code from stackoverflow, which is the same. But nobody ever argued that it has no uses in coding because you still have to read the code.

Honestly at this point any article just flat out dismissing LLMs for coding only reads to me like the author isn’t even trying to stay up to date. Which is understandable if they don’t like AI but makes posting about it a bit pointless.

A year ago I would had a similar opinion as the author but in the last 3-4 months specifically, it feels like AI based tools made a huge leap. I went from using short snippets for learning to letting AI implement entire features and being actually happy with the result.

There is however still a pretty big difference between what it produces for common problems vs. what it produces for specialized difficult ones. It’s also inherently better at some languages than others based on the availability of up-to-date training material. So you need some amount of breadth in your projects to accurately judge it.

If you only try some AI service in free mode on one thing every month, for example, you’ll just have this very polarized opinion that’s either “AI is useless” or “AI can do everything”, but you won’t have a good idea of what it can and can’t do.

And sometimes it doesn't actually remove the snow.

hey thats why they are pedalling it to india to have the datacenters, india is already cooking and MODI wants to give tax holidays.

"doesn't work" doesn't mean the AI literally does not produce any output or do anything, it means it has so many flaws it's just a fundamentally bad technology to be using.

And don't worry, I've got sources.

LLMs still routinely hallucinate, and even implementations being used by AI safety researchers can't help but automatically wipe email inboxes without permission. They atrophy your brain the longer you use them, cause both general dependency and emotional dependency, as well as deskill you at your job, they produce content favored worse by both humans and the AI models searching for trustworthy sources, and to top it all off, scaling laws are already failing to improve AI models enough to fix these problems, companies aren't seeing returns, the economy gained essentially nothing from AI investment, usage, and growth, and public perception by the people actually affected most by AI is only getting worse while the people financially incentivized to keep building it say it's going to get better, all while datacenters accelerate global warming and LLMs keep killing people.

I don't know about you, but I'd rather not support a technology that makes you get fundamentally worse at most cognitive tasks, damages the planet, burns money that could otherwise go to something more valuable, all while randomly killing mentally vulnerable people.

Nobody needs to hear about your ai girlfriend.

I have a theory that supporters of genAI or LLMs are lonely angry neets who just want a sense of control in their radically tumultuous lives.

care to weigh in on my theory of when AI started to help out with this moment in your life?

You're not a detail orientated person, are you?

Thanks for being the example for us