[SoftTalker]

I use AI for very little but I do like using it for stuff I'm just not very interested in but have to get done.

For programming, I don't like it. It's like a master carpenter building furniture from IKEA. Sure it's faster and he doesn't have to think very hard and the end result is acceptable but he feels lazy and after a while he feels like he is losing his skills.

The best days of computing for me were what you remember. A computer was just a blank slate. You turned it on, and had a ">" blinking on the screen. If you wanted it to do anything you had to write a program. And learning how to do that meant practice and study and reading... there were no shortcuts. It was challenging and frustrating and fun.

[mgfist]

All fair, but I think a different interpretation could be that AI allows you to vastly expand the scope of the possible, such to create a situation again where things are challenging and frustrating and fun.

[galaxy_tx]

This is the part that interests me most. The IKEA analogy from the parent comment assumes the carpenter's only option is to build the same furniture faster. But what if the carpenter uses the prefab stuff for the boring parts and spends their real energy on the joints and details that actually matter?

I've noticed this pattern in music too - the people who understand theory deeply use generative tools in ways that beginners literally can't, because they know which output to keep and which to throw away. The tool doesn't replace the taste, it just gives you more raw material to apply taste to.

But here's what I keep wondering: does expanding the scope of the possible eventually erode the deep understanding that makes the expansion valuable in the first place? Like, if you never have to debug a memory leak because the agent handles it, do you lose the intuition that would let you architect systems that don't leak in the first place?

[amelius]

Most programmers don't like the fuzziness of AI, so things may be challenging and frustrating, but certainly not fun.