Depends on the problem. If the complexity of what you are solving is in the business logic or, generally low, you are absolutely right. Manually coding a signup flow #875 is not my idea of fun either. But if the complexity is in the implementation, it’s different. Doing complex cryptography, doing performance optimization or near-hardware stuff is just a different class of problems.

> If the complexity of what you are solving is in the business logic or, generally low, you are absolutely right.

The problem is rather that programmers who work on business logic often hate programmers who are actually capable of seeing (often mathematical) patterns in the business logic that could be abstracted away; in other words: many business logic programmers hate abstract mathematical stuff.

So, in my opinion/experience this is a very self-inflected problem that arises from the whole culture around business logic and business logic programming.

Coding signup flow #875 should as easy as using a snippet tool or a code generator. Everyone that explains why using an LLM is a good idea always sound like living in the stone age of programming. There are already industrial level tools to get things done faster. Often so fast that I feel time being wasted describing it in english.

In my experience AI is pretty good at performance optimizations as long as you know what to ask for.

Can't speak to firmware code or complex cryptography but my hunch is if it's in it's training dataset and you know enough to guide it, it's generally pretty useful.