←back to thread

Ask HN: Has AI stolen the satisfaction from programming?

97 points marxism | 1 comments | 13 Oct 25 19:07 UTC | HN request time: 0.2s | source

I've been trying to articulate why coding feels less pleasant now.

The problem: You can't win anymore.

The old way: You'd think about the problem. Draw some diagrams. Understand what you're actually trying to do. Then write the code. Understanding was mandatory. You solved it.

The new way: The entire premise of AI coding tools is to automate the thinking, not just the typing. You're supposed to describe a problem and get a solution without understanding the details. That's the labor-saving promise.

So I feel pressure to always, always, start by info dumping the problem description to AI and gamble for a one-shot. Voice transcription for 10 minutes, hit send, hope I get something first try, if not hope I can iterate until something works. And when even something does work = zero satisfaction because I don't have the same depth of understanding of the solution. Its no longer my code, my idea. It's just some code I found online. `import solution from chatgpt`

If I think about the problem, I feel inefficient. "Why did you waste 2 hours on that? AI would've done it in 10 minutes."

If I use AI to help, the work doesn't feel like mine. When I show it to anyone, the implicit response is: "Yeah, I could've prompted for that too."

The steering and judgment I apply to AI outputs is invisible. Nobody sees which suggestions I rejected, how I refined the prompts, or what decisions I made. So all credit flows to the AI by default.

The result: Nothing feels satisfying anymore. Every problem I solve by hand feels too slow. Every problem I solve with AI feels like it doesn't count. There's this constant background feeling that whatever I just did, someone else would've done it better and faster.

I was thinking of all the classic exploratory learning blog posts. Things that sounded fun. Writing a toy database to understand how they work, implementing a small Redis clone. Now that feels stupid. Like I'd be wasting time on details the AI is supposed to handle. It bothers me that my reaction to these blog posts has changed so much. 3 years ago I would be bookmarking a blog post to try it out for myself that weekend. Now those 200 lines of simple code feels only one sentence prompt away and thus waste of time.

Am I alone in this?

Does anyone else feel this pressure to skip understanding? Where thinking feels like you're not using the tool correctly? In the old days, I understood every problem I worked on. Now I feel pressure to skip understanding and just ship. I hate it.

Show context
alganet ◴[13 Oct 25 19:37 UTC] No.45572458[source]▶
Think of it this way: if your problem can be solved by an LLM with the same quality, then it's not a problem worthy of a human to tackle. It probably never was in the first place, we just didn't knew.

The only exception here is learning (solving a solved problem so you can internalize it).

There are tons of problems that LLMs can't tackle. I chose two of those (polyglot programs, already worked on them before AI) and bootstrapping from source (AI can't even understand what the problem is). The progress I can get on those areas is not improved by using LLMs, and it feels good. I am sure there are many more of such problems out there.

replies(1): >>45572598 #
marxism ◴[13 Oct 25 19:51 UTC] No.45572598[source]▶
I actually agree with everything you said, and I see I failed to communicate my idea that's exactly why I'm so upset.

You said "the only exception here is learning" - and that exception was my hobby. Programming simple things wasn't work for me. It was entertainment. It was what I did for fun on weekends.

Reading a blog post about writing a toy database or a parser combinator library and then spending a Saturday afternoon implementing it myself. that was like going to an amusement park. It was a few hours of enjoyable, bounded exploration. I could follow my curiosity, learn something new, and have fun doing it.

And you're right: if an LLM can solve it with the same quality, it's not a problem worthy of human effort. I agree with that logic. I've internalized it from years in the industry, from working with AI, from learning to make decisions about what to spend time on.

But here's what's been lost: that logic has closed the amusement park. All those simple, fun learning projects now feel stupid. When I see those blog posts now, my gut reaction is "why would I waste time on that? That's one prompt away." The feeling that it's "not worthy" has completely drained the joy out of it.

I can't turn off that instinct anymore. I know those 200 lines of code are trivial. I know AI can generate them. And so doing it myself feels like I'm deliberately choosing to be inefficient, like I'm LARPing at being a programmer instead of actually learning something valuable.

The problem isn't that I disagree with you. The problem is that I agree with you so completely that I can no longer have fun. The only "worthy" problems left are the hard ones AI can't do. But those require months of serious investment, not a casual Saturday afternoon.

replies(3): >>45572762 #>>45572818 #>>45573035 #
1. alganet ◴[13 Oct 25 20:10 UTC] No.45572818[source]▶
I genuinely do not understand this. You can totally still do that for learning purposes.

The only thing you cannot do anymore is show off such projects. The portfolio of mini-tutorials is definitely a bygone concept. I actually like that part of how the culture has changed.

Another interesting challenge is to set yourself up to outperform the LLM. Golf with it. LLM can do a parser? Okay, I'll make a faster one instead. Less lines of code. There's tons of learning opportunities in that.

> The only "worthy" problems left are the hard ones

That's not true. There are also unexplored problems which the AI doesn't have enough training data to be useful.