Like... um... Well, maybe we will find them one day if we just keep wasting resources.

I started teaching myself guitar when I was 14. (I'm 78 now). I could have just bought records and listened to other guitarists. But I would have missed out on so much learning, fun times teaching guitar, and a lifetime of wonderful musical memories. Humans are meant to learn and often that means learning by doing--struggle, fail, keep trying, learn, succeed. If we're just button pushers and prompt writers, there's not much point in working. And who's going to rescue us when stuff breaks?

But rhere are valid reasons for reimplementing stuff, however. For example, the numerics world is really happy Eigen came about because some guy saw Lapack and said yuck. And Lapack is *very* uh, "good".

Or sometimes libraries do something pretty small, and is the dependency worth saving a day of implementation?

@cpr320 @brettcodes

– If you just glue libraries together, your code seems to be not that complex. This doesn't apply to all projects. There are pretty complex apps where you still get your share of custom code
– You can blame the library but you can blame your own code. LLMs can't take responsibilities, you have to sign-off on them.

4/4

– The entire point of using libraries is that you don't have to maintain them because someone (usually responsible) takes care of it for you. But you still have to maintain LLM-generated code yourself even if you use an LLM for code maintenance
– You can still contribute to open-source libraries

3/

2/

1/

The people also using the AI think they’re better than they are, which lowers the overall quality and turns the industry into a black hole of sunken costs.

But for what it's worth, I think your own observation demonstrates that you made the right choice: "I had a conversation with management about how a developer's job is now is to teach the AI to be better, make fewer mistakes, etc."

Sounds to me like you were training your replacement.

It's pointless for the purpose of creating a library.

But It's extremely valuable to have done it. You can judge the libraries you use. You have a deep sense of why the API is like it is. you're a much better user of the libraries.

LLMs try to prevent you from being better. And literature indicates they're making you worse.
@brettcodes

That was OK for the purpose. Today, depending on the specifics, I'd use my code or a library depending on whether dependencies or performance edged it. I have the *choice*.

LLMs will never give you that choice.

So the code will be worse.
@brettcodes

When I started seriously programming, back on the 1980s, I wrote a lot of libraries. If it was a numerical computation, I'd read the academic paper, implement it, test it and fix all the bugs I'd written. Then use it and rewrite or debug some more. I was **proud** of those libraries.

Then, the Internet and numpy happened, and all of a sudden, I didn't need to write numeric libraries any more. It hurt. I felt that I was reduced to gluing libraries together. I couldn't do the "real" coding any more.

But life goes on, and I mostly use scipy these days. I still itch to do some real coding sometimes. But I get more done, with fewer bugs. And my job is to solve problems, not to write another Runge-Kutta implementation.
I dislike trusting library code I didn't write, but I do, because that's how you got stuff done in 2024.

And I see AI coding as another, similar revolution. I'm depending more on code that something else /someone else wrote. It's like the library revolution all over again.

And I'm not a worse programmer because I use libraries. Different, though.

WTF would I (or anyone) pay to become a worse programmer when they can become a better one for free? *Without the cognitive risk*.

*Even* if it worked as advertised, it would make no sense versus training an intern.
@brettcodes