So im having a “issue” that might not be an issue? Ill explain.

Most of work is going full AI. We have around 20 developers. Its about 3/4 that are using AI to do ALL the work with Claude. Earlier in the year, everyone got a ton of AI credits and the amount of “Finished” products have popped out in mass. The amount of projects we have had is skyrocketing.

Now for the problem. Half the projects have terrible bugs. Pages that go no where, bugs that are VERY hard to find in the code (because its filled with code smells). And sometimes the site/program/etc… will just stop working for no reason because they decided to use some old version of react instead of anything modern. Because AI.

Even the ones that work will often be very difficult to debug if its just something the AI did or something the user did.

So a LOT of AI projects are getting abandoned…for more AI remake projects. I cant even call it iterations because no one learned anything making the last project.

Now once in a while I do use AI. It was part of my research back almost 20 years ago. But its mostly for one offs like creating a command line argument in python or give the the reference page for xyz feature. But I dont have it write the entire codebase for me. Seems like a recipe for disaster. And ive seen it bork a couple of peoples machines before.

I dunno am I the old man yells at clouds now?

  • assaultpotato@sh.itjust.works
    0·
    8 days ago

    So, here’s where I think I’m gonna lose you. These days I read diffs but I so rarely read entire files. I generally know how pieces of things fit together, and I generally know how the systems are architected, the tech stacks, and I can still read functions and syntax… but I wouldn’t say I “know how it works” at a code level at this point. Once I accepted that it’s OK to know the high level, and verify the diff/PR level, it’s OK to not have 100% awareness on implementation, using claude became a lot less… smelly to me.

    It’s not an easy thing to let go of, but the reality that I’ve experienced is that generally, claude can write good, secure functions. From a purely mechanical perspective, it’ll probably do a better job than I would on syntax, knowing the nooks and crannies of libraries, etc. But I review the diffs to be sure. However, I, the human, know what I want and generally how it should be done.

    I’d say that learning where to not bother with claude and where it works well was a bit of a thing to figure out, but I really don’t spend hours debugging claude slop. Cause honestly in qualified hands, it doesn’t really write slop. It does write slop if you let it, or ask it to take on too much scope, but… “work this ticket for me, pay attention to x y z and don’t change a b or c” is well within a reasonable model’s capabilities.

    I’d never pressure anyone into using LLMs and I have large ethical issues with the industry, but the idea that claude only slops doesn’t match with my lived experience in the past 6 months. I suspect when the finances of this whole thing go boom, KIMI and other open source models are gonna be able to run on rented GPUs for relatively cheap. Deepseek’s (reported) profit margins on inference seem to pay for the hardware (inc. GPU) in months… $1.6M per card in 5 years for revenue (not profit).

    Obviously these models are not intelligent and cannot be, but they can be very powerful code generators.