Ask HN: Has AI stolen the satisfaction from programming?

> 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.

Why didn't the fact that Redis already existed make the whole thing feel pointless before? You could just go to github and copy the thing. I don't get why AI is any different in this regard.

Here is how I'm using it:

Do all the stuff you mention the old way. If I have a specific, crappy API that I have to deal with, I'll ask AI to generate the specific functionality I want with it (no more than a method or two). When it comes to testing, I'll write a few tests (some simple, some complicated) and then ask AI to generate a set of tests based on those examples. I then run and audit the tests to make sure they are sensible. I always end my prompts with "use the simplest, minimal code possible"

I am mostly keeping the joy of programming while still being more productive in areas I'm not great at (exhaustive testing, having patience with crappy APIs)

Not world changing, but it has increased my productivity I think.

Not at all, most programming jobs are more about getting things done than the satisfaction of creating some programming master piece. You are assigned a part of the cog and you a responsible to get it done ASAP. It's a blue collar job under the guise of a white collar job. So it's nice to get a machine to do the grunt work while you decide how the code is supposed to function.

My experience with Vibe coding has been more frustrating than fruitful. Currently, I've only been fully successful with small code snippets and scripts but I can see where it's heading.

It works for me.

Reading HN I seem to be in the minority but AI has made programming a lot more fun for me. I've been an engineer for nearly 25 years and 95% of the work is rather mindless boilerplate. I know exactly what I need to do next, it just takes time and iteration.

The "you think about the problem and draw diagrams" part of you describe probably makes up less than 5% of a typical engineering workflow, depending on what you work on. I work in a scientific field where it's probably more than for someone working in web dev, but even here it's very little, and usually only at the beginning of a project. Afterwards it's all about iteration. And using AI doesn't change that part at all, you still need to design the high level solution for an LLM to produce anything remotely useful.

I never encountered the problem of not understanding details of the AI's implementation that people here seem to describe. I still review all the code and need to ask the LLM to make small adjustments if I'm not happy with it, especially around not-so-elegant abstractions.

Tasks that I actively avoided previously because they seemed like a hassle, like large refactorings, I no longer avoid now because I can ask an AI to do most of it. I feel so much productive and work is more satisfying because I get to knock out all these chores that I had resistance to before.

Brainstorming with an AI about potential solutions to a hard problem is also more fun for me, and more productive, than doing research the old ways. So instead of drawing diagrams I now just have conversations.

I can't say for certain whether using LLMs has made me much more productive (overall it likely has but for certain tasks it hasn't), but it definitely has made work more fun for me.

Another side effect has been that I'm learning new things more frequently when using AI. When I brainstorm solutions with an AI or ask for an implementation, it sometimes uses libraries and abstractions I have not seen before, especially around very low level code that I'm not super familiar with. Previously I was much more likely to use or do things the one way I know.

It's the reason I won't use AI, the hard work and sometimes grim satisfaction from solving a problem is what makes it worth it