I'd argue that it's actually a benefit; I like that I can do several generations and compare them and pick the best result. HP, for example, used to do this with software teams, and that's how we got Rocky Mountain BASIC (AIUI the competing team was East Coast BASIC).

In computing, things are much more useful when they behave in predictable ways. Even AI, many (most?) would argue.

One can’t write anything efficient without comp-sci being forefront in your mind the entire time you are writing. Which explains exactly why everything is so slow today.

If you’re not thinking about what is computable, what is not computable, and what is easily computable as you think about the problems you are trying to solve, you are a professional novice.

You definitely don't need to study computer science just to avoid making common performance issues and in fact just studying computer science doesn't mean that you aren't going to introduce things like N+1 query issues, that's sort of thing comes from experience more than anything.

Likewise, just studying computer science does not mean that you are going to be well suited for software development in the real world.

> If you’re not thinking about what is computable, what is not computable, and what is easily computable as you think about the problems you are trying to solve, you are a professional novice.

Of course I consider all of these things but that didn't come from studying computer science in college lol.