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- Hacker News
- The biggest problem with AI isn't being able to do things. You can do them. The question is "should you?" I had a peer dev this week put in a commit that was 1.2mb (this despite an AGENTS.md saying not to do exactly this) of plan documents and ~20 lines of code. The conversation on the PR review was probably one of the best learning experiences for both of us. It was all about the ramifications of a book's worth of AI pontificating about what it would do and what succeeded and what failed. And we were able to validate that that plan document had huge side effects as we prompted with it in the repo. As we read the document we realized that it was just 1.2MB of smart sounding gibberish and maybe two bullet points of signal.by indymike
- One very unfortunate curse we are stuck with is LLM providers pulling the rug from under us and swapping models with quantized versions during peak demand or on monthly plans. You never know if that's the reason AI starts writing shitty code or it's just the context size that has grown. On top of that there is the queuing mechanism which makes tasks take longer. Sometimes AI is super fast and sometimes a simple task takes 10, 15 or even 20 minutes of "thinking". You may not realize this if you are just using your same subscription but if you switch between providers you can immediately tell. I advise everyone to invest $5 in openrouter, deepseek and qwencode. Just do an experiment and use same model (deepseek-4.1 flash) asking same prompt on same code, then look at the result. Spoiler: you will see trash coming out of openrouter at 1-5 tokens/second, you will see slightly faster and better quality output from qwencloud and when you get to deepseek API where you are paying per token you will not believe this is the same model. Because it isn't.by elwebmaster
- I also had similar feelings recently. I think the article is good and captures many of the issues I have with the current state of AI development, but I feel like the conclusion/reaction is somewhat exaggerated.
Of course if someone wants to stop using AI completely that's a completely valid decision[0], but I somewhat feel like AI is just a tool that can be easily misused.
I constantly have to review giant PRs and I noticed that I'm handwaving them more and more often. We went from almost no commit messages to walls of text that no one reads. We're starting to become bottlenecked on reviews because code is coming out too fast.
But at the same time, these are mostly issues stemming from a lack of understanding of why some of the standards/processes existed in the first place. If a developer thinks the commits have to be written just to tick a checkbox, they won't care about making them readable.
And at the same time, I'm getting a lot of value from AI, in tasks that do not necessarily have such adverse effects:
- I can create quick tools to test something, or parse/process some data. In these instances code quality is not important and I don't really want to spend hours on developing it myself (just to feel accomplished?)
- I can research issues in our codebase by just providing a log file. It's not always gonna be accurate or correct but it often gives me a very good starting point, almost always quicker than I could've done it myself
- While I do not use AI to completely generate ticket descriptions, asking it to generate me a body containing the relevant code snippets and references allows me to focus on verifying that what I'm writing is correct and understandable.
Etc etc.
So I don't know if it's just the nature of my work, the fact that I have a different skillset, or different priorities. But it somehow feels weird to me wanting to completely abandon AI just because in some cases it can lead to frustrating consequences.
[0]: I too just started a new project where I'm forcing myself to use absolutely no AI!
by thevinter - I sometimes look at it via the metaphor of music.
Playing an instrument vs electronic/computer music.
We do forget skills we don't practice, especially fine motor skills (like playing the guitar or typing code).
There's inherent pleasure in playing a musical instrument - practicing improves fine motor skills and produces satisfaction.
You can play for yourself and that can be a great experience.
Often people create music for other listeners - and now the satisfaction comes not just from your skill, but from how the music impacts your listeners.
They say you can put more of your 'soul' into music made with an instrument, but I'd say there's quite a bit of electronic music with just as much soul.
People who create electronic music don't generate any of those sounds with their fine motor skills, but they do have a plan about how the song progresses and what emotional state it elicits in users.
That's why you have DJs which are more popular than others.
If you stop playing the guitar for a year, then pick it up and try playing something, you will feel very rusty. But give it a week of practice and most of your skill comes back.. and in 1 month you're back to your peak skill.
I guess my point is - If you go full on agentic, you'll loose some of your coding skill, but you can get it back fairly quickly if you go back to manual coding. On the flip side, you get better at using AI if you use it, so your thinking is at a higher level, but you give up understanding the low level details of how exactly the code works.
Either way you're making 'music', albeit a different kind of music.
by delegate - “ There were tasks I could have done in 20 minutes easily, that took 5 minutes of an AI agent, and then 2 days for me to review.”
This is using AI for productivity in any domain, in a nutshell. I just wrote a book using Claude as an experiment, and while the thing got done and it was an amazing tool and a great experience, what I’m left with is a book where every line needs rewriting, there are logical inconsistencies throughout, and the style is so bad it should actually just be binned rather than rewritten.
by gizajob - Yeah, I have never understood the over reliance on AI. Writing the code is not the challenge. The time it takes to push a new feature and test it out is often trivial, maybe a few hours.
The real challenge is forming the new ideas in the first place and most of those new ideas coming either from using the code as a product or time spent maintaining and refactoring large code.
Anyways, if you want to continue on the path towards regaining control and take it to the next level I wrote something similar here: https://blog.sharefile.systems/be-brave-go-low/
- My employer pays for Claude, and my approach is to use it as a better Google search. It's often not better.
Just today it made three glaring mistakes in one session:
1. It read a file in the wrong directory, because that file had the same name as the file in the right directory. It apologized when I challenged it, promising me that it would remember to "read import statements" in the future.
2. It miscounted the number of times a function was called in my repo. It said 20, while my built-in IDE search accurately showed 17. Again, it apologized when I corrected it.
3. It referred to a variable by name that does not exist anywhere in my code. It apologized, and said it was referring to a variable used internally by one of the third-party packages installed in my repo.
So many apologies.
It's the little things like this that remind me on a regular basis just how little I can trust artificial "intelligence."
by stack_framer - I find it strange to see people writing articles like this as if everyone has used AI for decades. I've programmed for decades. I thought I retired three years ago but got an offer I couldn't refuse. Already there were little things I'd forgotten how to use.
Over the past six months I tried using Claude, chatgpt, Grok and Gemini. At best I got reminders of how things worked. People online say they use them to write their code. The code they supplied to me has NEVER worked or was so convoluted that I threw it away and did it myself.
At most, I use these tools as search engines. Even then some references are poor.
I'm starting to think this is becoming a sad, sad world and AI is just the new TV of the programming world.