I generally do have that mindset, but over the past 1y of Claude code I do notice that I’m clearly losing my understanding of the internals of projects. I do review LLM generated code, understand it, no problem reading/following through. But then someone asks me a question, and I’m like… wait, I actually don’t know. I remember the instructions I gave and reviewing the code but don’t actually have a fine-details model of the actual implementation crystallized in my mind, I need to check, was that thing implemented the way I thought it was or not? Wait, it’s actually wrong/not matching at all what I thought! It’s definitely becoming uncomfortable and makes me reconsider my use of Claude code pretty significantly

One-off tasks and parts of the stack that already have lots of disposable code do not need the same scrutiny as everything else. Just as there is a broad continuum of code importance, there is a broad continuum of testing requirements, and this was the case before AI. Keeping this in mind, AIs can also do some verification and testing, too.