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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.

1. agentultra ◴[13 Oct 25 19:55 UTC] No.45572632[source]▶
Can’t be disappointed if you don’t use it.

I’ve never met so many people that hate programming so much.

You get the same thing with artists. Some product manager executive thinks their ideas are what people value. Automating away the frustration of having to manage skilled workers is costly and annoying. Nobody cares how it was made. They only care about the end result. You’re not an artist if all you had to do was write a prompt.

Every AI-bro rant is about how capital-inefficient humans are. About how fallible we are. About how replaceable we are.

The whole aesthetic has a, “good art vs. bad art,” parallel to it. Where people who think for themselves and write code in service of their work and curiosity are displayed as inferior and unfit. Anyone who is using AI workflows are proper and good. If you are not developing software using this methodology then you are a relic, unfit, unstable, and undesirable.

Of course it’s all predicated in being dependent on a big tech firm, paying subscription fees and tokens to take a gamble at the AI slot machine in hopes that you’ll get a program that works the way you want it to.

Just don’t play the game. Keep writing useless programs by hand. Implement a hash table in C or assembly if you want. Write a parser for a data format you use. Make a Doom clone. Keep learning and having fun. Satisfaction comes from mastery and understanding.

Understanding fundamental algorithms, data structures, and program composition never gets old. We still use algebra today. That stuff is hundreds of years old.