i had this same complaint but no offense to you it turned out i was just not using the models right.

ai llm are doing what i tell them to.

if you’re building something meaningful (in my case a platform used by many people across many companies) you want to ensure you

1. have actual systems engineering and architecture in mind that you want the models to

2. implement based on what you tell it to do

when i was just telling the models what i want done without doing due diligence it would go and do some moronic implementation that was awful. mid input = mid output

these days i just maintain specifications documents and the AI follows everything i tell it to in that document. so when i tell it to dos one thing, the result is made following those architecture specs.

i have code that is single resp, modular, easy to extend and test.

i would ballpark 95% of the time i get what i asked for.

sometimes it tries to be clever in cases that weren’t covered in my arch specs. in those 5% of cases i go and update my specs.

source: used billions of tokens worth to build something actually in production across both mobile platforms and web, deployed on my own cloud infra. i use codex mainly. some claude.