I don’t really agree, I think that’s kind of a problem with approaching it. I’ve built some pretty large projects with AI, but the thing is, you have to approach it the same way you should be approaching larger projects to begin with - you need to break it down into smaller steps/parts.
Comment on I Went All-In on AI. The MIT Study Is Right.
Suffa@lemmy.wtf 5 days ago
AI is really great for small apps. I’ve saved so many hours over weekends that would otherwise be spent coding a small thing I need a few times whereas now I can get an AI to spit it out for me.
But anything big and it’s fucking stupid, it cannot track large projects at all.
ipkpjersi@lemmy.ml 4 days ago
victorz@lemmy.world 5 days ago
What kind of small things have you vibed out that you needed?
MrScottyTay@sh.itjust.works 5 days ago
Encryption, login systems and pricing algorithms. Just the small annoying things /s
utopiah@lemmy.world 5 days ago
FWIW that’s a good question but IMHO the better question is :
What kind of small things have you vibed out that you needed that didn’t actually exist or at least you couldn’t find after a 5min search on open source forges like CodeBerg, Gitblab, Github, etc?
Because making something quick that kind of works is nice… but why even do so in the first place if it’s already out there, maybe maintained but at least tested?
victorz@lemmy.world 5 days ago
Since you put such emphasis on “better”: I’d still like to have an answer to the one I posed.
Yours would be a reasonable follow-up question if we noticed that their vibed projects are utilities already available in the ecosystem. 👍
utopiah@lemmy.world 5 days ago
Sure, you’re right, I just worry (maybe needlessly) about people re-inventing the wheel because it’s “easier” than searching without properly understand the cost of the entire process.
lepinkainen@lemmy.world 5 days ago
What if I can find it but it’s either shit or bloated for my needs?
utopiah@lemmy.world 5 days ago
Open an issue to explain why it’s not enough for you? If you can make a PR for it that actually implements the things you need?
My point to say everything is already out there and perfectly fits your need, only that a LOT is already out there. If all re-invent the wheel in our own corner it’s basically impossible to learn from each other.
jj4211@lemmy.world 5 days ago
So if it can be vibe coded, it’s pretty much certainly already a “thing”, but with some awkwardness.
Maybe what you need is a combination of two utilities, maybe the interface is very awkward for your use case, maybe you have to make a tiny compromise because it doesn’t quite match.
Maybe you want a little utility to do stuff with media. Now you could navigate your way through ffmpeg and mkvextract, which together handles what you want, with some scripting to keep you from having to remember the specific way to do things in the myriad of stuff those utilities do. An LLM could probably knock that script out for you quickly without having to delve too deeply into the documentation for the projects.
MangoCats@feddit.it 4 days ago
I’ll put it this way: LLMs have been getting pretty good at translation over the past 20 years. Sure, human translators still look down their noses at “automated translations” but, in the real world, an automated translation gets the job done well enough most of the time.
LLMs are also pretty good at translating code, say from C++ to Rust. Not million line code bases, but the little concepts they can do pretty well.
On a completely different tack, I’ve been pretty happy with LLM generated parsers. Like: I’ve got 1000 log files here, and I want to know how many times these lines appear. You’ve got grep for that. But, write me a utility that finds all occurrences of these lines, reads the time stamps, and then searches for any occurrences of these other lines within +/- 1 minute of the first ones… grep can’t really do that, but a 5 minute vibe coded parser can.
utopiah@lemmy.world 5 days ago
If I understand correctly then this means mostly adapting the interface?
MangoCats@feddit.it 4 days ago
In a sense, this is what LLMs are doing for you: regurgitating stuff that’s already out there. But… they are “bright” enough to remix the various bits into custom solutions. So there might already be a NWS API access app example, and a Waveshare display example, and so on, but there’s not a specific example that codes up a local weather display for the time period and parameters you want to see (like, temperature and precipitation every 15 minutes for the next 12 hours at a specific location) on the particular display you have. Oh, and would you rather build that in C++ instead of Python? Yeah, LLMs are actually pretty good at remixing little stuff like that into things you’re not going to find exact examples of ready to your spec.
ipkpjersi@lemmy.ml 4 days ago
I built a MAL clone using AI, nearly 700 commits of AI. Obviously I was responsible for the quality of the output and reviewing and testing that it all works as expected, and leading it in the right direction when going down the wrong path, but it wrote all of the code for me.
There are other MAL clones out there, but none of them do everything I wanted, so that’s why I built my own project. It started off as an inside joke with a friend, and eventually materialized as an actual production-ready project.
6nk06@sh.itjust.works 5 days ago
I’m curious about that too since you can “create” most small applications with a few lines of Bash, pipes, and all the available tools on Linux.
victorz@lemmy.world 5 days ago
Maybe they don’t run Linux. 🤭
mjr@infosec.pub 4 days ago
Perverts!
MangoCats@feddit.it 4 days ago
Depends on how demanding you are about your application deployment and finishing.
Do you want that running on an embedded system with specific display hardware?
Do you want that output styled a certain way?
AI/LLM are getting pretty good at taking those few lines of Bash, pipes and other tools’ concepts, translating them to a Rust, or C++, or Python, or what have you app and running them in very specific environments. I have been shocked at how quickly and well Claude Sonnet styled an interface for me, based on a cell phone snap shot of a screen that I gave it with the prompt “style the interface like this.”
CrabAndBroom@lemmy.ml 5 days ago
Not OP but I made a little menu thing for launching VMs and a script for grabbing trailers for downloaded movies that reads the name of the folder, finds the trailer and uses yt-dlp to grab it, puts it in the folder and renames it.
victorz@lemmy.world 5 days ago
Definitely sounds like a tiny shell script but yeah, I guess it’s seconds with an agent rather than a few minutes with manual coding 👍
Nalivai@lemmy.world 5 days ago
It never seconds. The first three versions will don’t do what you want (or not work at all), so you will end up arguing with this shit for significant amount of time without realising it
CrabAndBroom@lemmy.ml 5 days ago
Yeah pretty much! TBH for the first one there are already things online that can do that, I just wanted to test how the AI would do so I gave it a simple thing, it worked well and so I kept using it. The second one I wasn’t sure about because it’s a bit copyright-y, but yeah like you say it was just quicker. I wouldn’t use the AI for anything super important, but I figured it’d do for a quick little script that only needs to do one specific thing just for me.
MangoCats@feddit.it 4 days ago
I have a little display on the back of a Raspberry Pi Zero W - it recoded that display software to refresh 5x faster, and it updated the content source to move from Meteomatics (who just discontinued their free API) to the National Weather Service.