Not so long ago I read something on HN which resonated with me: we’re moving into the era that is comparable to car mechanics enthusiasts. You have a previous generation of cars where people just enjoy working on with hand tools, and there’s modern cars where people like to tune with software patches.
From the very start of llms I’ve had nothing but bad experiences with code that was generated for me. Either it’s buggy, it works but I end up losing an evening on some obscure bug, or it’s full of red flags.
My latest hobby project is just in a text editor with markup and that’s it. I’m also done with the augmented assistance in the IDE. I google things I forgot. I constantly read these amazing stories of people vibe-coding some firmware/driver that just works, and honestly I’m starting to question whether I’m reading the posts of some promotional bot.
> I constantly read these amazing stories of people vibe-coding some firmware/driver that just works, and honestly I’m starting to question whether I’m reading the posts of some promotional bot.
No, it just works after a few iterations.
And you'd know this if you would use AI instead of working in a text editor with markup.
To each their own, and I understand if working by hand is more fun for you.
But in my opinion you guys don't get to make strong claims about the quality of works that make heavy use of AI.
You don't have the experience, and I bet neither does the guy who wrote the article about it being essential to handwrite all the code after planning. The arguments about the environment and sustainability do not seem relevant.
Yeah I don’t understand. This is late 2026. Opus 5.5 can literally build anything I throw at it. We’re still seeing people who have not been satisfied with _any_ AI generated code?
I've thrown a 20 year old .net 4.8 codebase that's a mixture of proprietary sdks and legacy code and LLMs choke. Building some greenfield pieces for the same application works great so far though.
I've also made some plugins for some hobby software with very limited viewing of source code that I'm very happy with.
people get AI psychosis because they see tailwind-infused gradient dashboards and think every codebase has much smaller problems than this, so AI can build everything else
we have a 6 year old codebase with pretty much everything proprietary and there's no AI that can keep up without having an entire team to create an in-house RAG and throw thousands per day in tokens and spend expensive developer time on reviewing and asking for stupid changes that don't fit in
these arguments would make much more sense if tokens were practically free and LLMs could run in pc graphics cards, but when the model requires a data center that can be seen in space just to give you 100 tokens per second then you're basically a car in 1900 when all the roads were dirt roads for horses
chicken-stew · · focus · HN ↗
From the very start of llms I’ve had nothing but bad experiences with code that was generated for me. Either it’s buggy, it works but I end up losing an evening on some obscure bug, or it’s full of red flags.
My latest hobby project is just in a text editor with markup and that’s it. I’m also done with the augmented assistance in the IDE. I google things I forgot. I constantly read these amazing stories of people vibe-coding some firmware/driver that just works, and honestly I’m starting to question whether I’m reading the posts of some promotional bot.
user43928 · · focus · HN ↗
No, it just works after a few iterations.
And you'd know this if you would use AI instead of working in a text editor with markup.
To each their own, and I understand if working by hand is more fun for you.
But in my opinion you guys don't get to make strong claims about the quality of works that make heavy use of AI.
You don't have the experience, and I bet neither does the guy who wrote the article about it being essential to handwrite all the code after planning. The arguments about the environment and sustainability do not seem relevant.
cdelsolar · · focus · HN ↗
parineum · · focus · HN ↗
I've thrown a 20 year old .net 4.8 codebase that's a mixture of proprietary sdks and legacy code and LLMs choke. Building some greenfield pieces for the same application works great so far though.
I've also made some plugins for some hobby software with very limited viewing of source code that I'm very happy with.
freecodeio · · focus · HN ↗
we have a 6 year old codebase with pretty much everything proprietary and there's no AI that can keep up without having an entire team to create an in-house RAG and throw thousands per day in tokens and spend expensive developer time on reviewing and asking for stupid changes that don't fit in
these arguments would make much more sense if tokens were practically free and LLMs could run in pc graphics cards, but when the model requires a data center that can be seen in space just to give you 100 tokens per second then you're basically a car in 1900 when all the roads were dirt roads for horses