Ask HN: Are developers sad about AI writing more of their code?

I think the real sadness is that many developers may stop learning the deeper fundamentals — the things that AI can't replace.

When people start relying on the "I just want it to work this way" mentality and let AI take over, they can lose track of how things actually work under the hood. And that opens the door to a lot of problems — not just bugs, but blind trust in things they don't understand.

For me, the joy is in understanding. Understanding what each part does, how it all fits together. If that disappears, I think we lose something important along the way.

I was scared of this initially, but I've found that I mostly just use it for tedious code that I would normally procrastinate just because of how mind numbing it was (like adding another CRUD endpoint) or making a sweeping change across code that wasn't as simple as a find and replace.

For things that keep me interested, I just won't use LLM features. Sometimes at the end I'll have it audit my code and sometimes it'll catch something that can be improved.

Also test cases. It's not perfect, but a large chunk of that being automated there is very nice.

if you think about it the resource wasteful approach pre-LLM didnt really make sense (thousands of people often times re-implementing similar use cases). LLMs are like global open source repositories of everything known to mankind with search on steroids. we can never go back, if only for this one reason (imagine of how many hours of peoples lives were lost implementing the same function, or yet another CRUD app)... so if we cant go back whats next?

the paradigm is shifting from us not deciding how to do, but deciding what to do, maybe by writing requirements and constraints and letting AI figure out the details.

the skill will be in using specific language with AI to get the desired behavior, old code as we know it is garbage, new code is writing requirements and constraints

so in a sense we will not be reviewers, nor architects or designers, but writers of requirements and use cases in a specific LLM language, which will have its own but different challenges too

there might be still a place for cream of the crop mega talented people to solve new puzzles (still with AI assistance) in order to generate new input knowledge to train LLMs

This is definitely the core issue from my perspective.

Yeah, that’s a fair point. Abstraction is part of progress — and we do rely more and more on things “just working.”

But that trust can be dangerous when we don’t even know what we’re trusting. And when something breaks, it can leave us completely blind.

I’m not saying everyone needs to go all the way down to the metal — but I do think it’s important to at least understand the boundaries. Know what’s underneath, even if you don’t touch it every day.

Otherwise, it’s not engineering anymore — it’s guessing.

And I’ve never been good at just “believing” things work. I need to poke around, break them, fix them. That’s how I learn. Maybe I’m just stubborn like that.