I think it's 5.

I was very impressed when I first started using AI tools. Felt like I could get so much more done.

A couple of embarrassing production incidents later, I no longer feel that way. I always tell myself that I will check the AI's output carefully, but then end up making mistakes that wouldn't have happened if I wrote the code myself.

This is what slows me down most. The initial implementation of a well defined task is almost always quite fast. But then it's a balance of either...

* Checking it closely myself, which sometimes takes just as long as it would have taken me to implement it in the first-place, with just about as much cognitive load since I now have to understand something I didn't write

* OR automating the checking by pouring on more AI, and that takes just as long or longer than it would have taken me to check it closely myself. Especially in cases where suddenly 1/3 of automated tests are failing and it either needs to find the underlying system it broke or iterate through all the tests and fix them.

Doing this iteratively has made the overall process for an app I'm trying to implement 100% using LLMs to take at least 3x longer than I would have built it myself. That said, it's unclear I would have kept building this app without using these tools. The process has kept me in the game - so there's definitely some value there that offsets the longer implementation time.