I get where you are coming from (it's me, last year), and that's what I thought.
But if you use Claude Code or Codex, you will blow through your pro plan quickly. If you don't use them, you are not really using AI. I know how that sounds, but that is how it is.
These models are smart now. Really smart. Yes, they hallucinate, but usually not without reason. I am having long discussions with these models before generating code, and generate markdown from them. These are then the basis for the generated code. I am trying to give the model as much background as possible. I read the generated markdown: if there is something that feels off, like I don't really know what it means, then you need to fix that first, by discussing it with the model. Often, these are real problems in how I was understanding something, the model wasn't really getting it, and just made something up that it hoped would kinda work.
And I prefer Codex over Claude Code (prior to Fable, Fable is something else!), it behaves more like a helpful PhD-level colleague and just feels sharper. Claude Code sounds a bit like a mix between an HR person and a therapist that is on vacation too often.
I am still looking at code, but only if something came up during high-level discussions with the model that I want to pin down exactly. Otherwise I just talk about the high-level intention of the code, usually not looking at it.
What REALLY helps is coming up with the right theoretical frameworks for your work, with practical implementations that the model can use, and that allow some kind of verification. Let's say you want to parse something. For a one-off the model is great at generating "hand-rolled" parsing code, but for something disciplined, giving the model a way to generate context-free grammars and giving it a way to check them for determinism gives great results.