Comment by josephg
5 days ago
> It works, sure, but is it worth your time to use?
This is something I like about the LLM future. I get to spend my time with users thinking about their needs and how the product itself could be improved. The AI can write all the CSS and sql queries or whatever to actually implement those features.
If the interesting thing about software is the code itself - like the concepts and so on, then yeah do that yourself. I like working with CRDTs because they’re a fun little puzzle. But most code isn’t like that. Most code just needs to move some text from over here to over there. For code like that, it’s the user experience that’s interesting. I’m happy to offload the grunt work to Claude.
Every little detail matters though. In SQL, do you want your database field to have limited length? If so, pay attention to validation, including cases where the field's content is built up in some other way than just entering text in a free-form text field (e.g. stuffing JSON into a database field). If not, make sure you don't use some generic "string" field type provided by your database abstraction layer that has an implicit limited length. Want to guess why that scenario's on my mind? Yeah, I neglected to pay attention to that detail, and an LLM might too. In CSS, little details affect the accessibility of the UI.
So we need to pay attention to every detail that doesn't have a single obviously correct answer, and keep the volume of code we're producing to a manageable enough level that we actually can pay attention to those details. In cases where one really is just literally moving data from here to there, then we should use reliable, deterministic code generation on top of a robust abstraction, e.g. Rust's serde, to take care of that gruntwork. Where that's not possible, there are details that need our attention. We shouldn't use unreliable statistical text generators to try to push past those details.
> So we need to pay attention to every detail that doesn't have a single obviously correct answer
I really, really wish that were the case. But look at the modern web. Look at iOS apps. Look at how long discord takes to launch on a modern computer. Look how big and slow everything is. Most end user applications released today do not pay attention to those small details. Definitely not in early versions of the software. And they're still successful. At least, successful enough.
I'd love a return to the "good old days" where we count bytes and make tight, fast software with tiny binaries that can perform well even on 20 year old computers. But I've been outvoted. There aren't enough skilled programmers who care about this stuff. So instead our super fast computers from the future run buggy junk.
Does claude even make worse choices than many of the engineers at these companies? I've worked with several junior engineers who I'd trust a lot less with small details than I trust claude. And thats claude in 2026. What about claude in 2031, or 2036. Its not that far away. Claude is getting better at software much faster than I am.
I don't think the modern software development world will make the sort of software that you and I would like to use. Who knows. Maybe LLMs will be what changes that.
> But look at the modern web. Look at iOS apps. Look at how long discord takes to launch on a modern computer. Look how big and slow everything is. Most end user applications released today do not pay attention to those small details. Definitely not in early versions of the software. And they're still successful. At least, successful enough.
The main issue is that we have a lot of good tech that are used incorrectly. Each components are sound, but the whole is complex and ungainly. They are code chimeras. Kinda like using a whole web browser to build a code editor, or using react as the view layer for a TUI, or adding a dependency just to check if a file is executable.
It's like the recently posted project which is a lisp where every function call spawn a docker container.
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