Comment by fzeroracer
5 days ago
Missing the forest for the trees here.
The benefit of writing your own first draft is the same reason why you take notes during classes or rephrase things in your head. You're building up a mental model of the codebase as you write it, so even if the first draft isn't great you know where the pieces are, what they should be doing and why they should be doing it. The cognitive benefits of writing notes is well known.
If you're using an AI to produce code you're not building up any model at all. You have to treat it as an adversarial process and heavily scrutinize/review the code it outputs, but more importantly it's code you didn't write and map. You might've wrote an extensive prompt detailing what you want to happen, but you don't know if it did happen or not.
You should start asking yourself how well you know the codebase and where the pieces are and what they do.
It really depends on the scale of the code you are asking it to produce. The sweet spot for me with current models is about 100-200 lines of code. At that scale I can prompt it to create a function and review and understand it much faster than doing it by hand. Basically using it as super super autocomplete, which may very well be underutilizing it, but at that scale, I am definitely more productive but still feel ownership of the end result.