Does the thing work like I want it in the end? Is it fast, reliable, enjoyable to use, maintainable, cheap, efficient, resilient, etc?

If so, I don't care if I wrote it by hand or with an LLM. People who think that building something with an LLM somehow dooms the something to mediocrity are engaging in magical thinking. I can simply use as much or as little LLM as will allow me to meet my quality criteria.

You forgot maintainable.

Added a few more adjectives and an "etc", to cover all pedantic bases that don't matter to my argument.

You listed "maintainable", but how do you know your project is maintainable, if you yourself have no understanding of the code base? Presumably the reason is that the AI has managed to maintain the project so far, so it follows that it will be able to do so in the future. But that's not a given. It's more of a prayer.

Well if you have experience reviewing other people’s code, it is not that different than finding an idea, asking copilot to do it, and then review just as if you had a ton of junior engineers to write code for you, which also can go too far in one direction before asking for feedback.

So it really depends on your reviewing ability how maintainable code you will get. It is a bit of effort to review something “you have done” as thoroughly as something a colleague have done. Somehow I still feel sense of ownership even though the LLM did it.

I like reviewing using GitHub’s interface, so I often do a thorough review in that familiar interface while the PR is still draft, and before I have invited others to review. If I review my own code directly in my editor when the agent is done, my brain isn’t in the right context and can get distracted or skip over something.