Comment by a_bonobo | Hacker News Reader

Comment by a_bonobo | Hacker News Reader

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Do you like 'solving problems' or do you like 'getting into the weeds'? Both are valid, and both are common uses of programming.

When I was younger, I loved 'getting into the weeds'. 'Oh, the audio broke? That gives me a great change to learn more about ALSA!'. Now that I'm older, I don't want to learn more about ALSA, I've seen enough. I'm now more in camp 'solving problems', I want the job done and the task successfully finished to a reasonable level of quality, I don't care which library or data structure was particularly used to get the job done. (both camps obviously overlap, many issues require getting into the weeds)

In this framework, the promise of AI is great for camp 'solving problems' (yes yes hallucinations etc.), but horrible for camp 'getting into the weeds'. From your framing you sound like you're from camp 'getting into the weeds', and that's fine too. But I can't say camp 'solving problems' doesn't like programming. Lot of carpenters out there who like to build things without caring what their hammer does.

>I'm now more in camp 'solving problems', I want the job done and the task successfully finished to a reasonable level of quality

To split the definitions one step further: That actually sounds not like you 'enjoy solving problems'(the process), but rather you 'enjoy not having the problem anymore'(the result).

Meaning you don't like programming for itself(anymore?), but merely see it as a useful tool. Implying that your life would be no less rich if you had a magical button that completely bypassed the activity.

I don't think someone who would stop doing it if given the chance can be said to "like programming", and certainly not in the way GP means.

AI is not "a magical button" though. It's another tool to solve the problem, that allows you to get a bit less into the weeds (sometimes, until it messes up), essentially by giving you a bunch of reasonable default behavior.

I spent a very long time getting into the weeds to learn everything about computer architecture, because at the time it seemed like it was the only way to do it and I wanted to have a career. In the meantime social media / cloud hosting / StackOverflow were invented, it became much easier for people to write online, and it turned out I didn't need to do any of that because the actual authors have all explained themselves on it.

Though, doing this is still the right way to learn how to debug things!

nb I actually just realized I never understood a specific bit of image processing math after working on ffmpeg for years, asked a random AI, and got a perfectly clear explanation of it.

I like solving problem. But I also want the problem to stay solved. And if I happen to see a common pattern between problems, then I build a solution generator.

Maybe because I don’t think in terms of code. I just have this mental image that is abstract, but is consistent. Code is just a tool to materialize it, just like words are a tool to tell a story. By the time I’m typing anything, I’m already fully aware of my goals. Designing and writing are two different activities.

Reading LLMs code is jarring because it changes the pattern midway. Like an author smashing the modern world and middle earth together. It’s like writing an urban fantasy and someone keeps interrupting you with some hard science-fiction ideas.

Exactly this. I still "get into the weeds" without AI if I really need to dig into learning something new or if I want to explore some totally new idea (LLMs don't really do "totally new"). If I'm debugging a CRUD app, though... eh, it's sunny outside and I only have a couple more hours of daylight, so, AI it is.

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