> Boilerplate and scaffolding

Have we really reached the limit of how much we can reliably automate these things via good old metaprogramming and/or generator scripts, without resorting to using unreliable and expensive statistical models via imprecise natural language?

> Refusing to use AI out of principle is as irrational as adopting it out of hype.

I'm not sure about this. For some people, holding consistently to a principle may be as satisfying, or even necessary, as the dopamine hit of creation mentioned in the article.

I spend a lot of time side by side with other devs watching them code and providing guidance. A trend I'm starting to sense is that developer velocity is just as much hindered by unfamiliarity with their tools as much as it is wrestling with the core problem they really want to solve.

When to use your mouse, when to use your keyboard, how to locate a file you want to look at in your terminal or IDE, how to find commands you executed last week, etc. It's all lacking. When devs struggle with these fundamentals, I suspect the desire to bypass all this with a singular "just ask the LLM" interface increases.

So when orgs focus on a "devs should use LLMs more to accelerate", I really wish the focus was more "find ways to accelerate", which could more reliably mean "get more proficient with your tools".

I think there's a lot of good that can be gained from formalizing conventions with templating engines (another tool worth learning), rather than relying on stochastic template generation.