This is an issue that's very real for me right now because I'm in the middle of teaching my own kids programming, and we've been working on it for years at this point. I'm watching AI seemingly invalidate the premise behind learning all of it. It's been a pretty depressing change to be honest, because I love programming and watching this happen is hard.
So, I've changed my approach with my own teaching. I'm having them do three things that I'm hoping will prepare them to work in the world they're going to be entering soon:
1. Always have a handmade project going, and work on it without AI assistance even if it's painfully slow.
2. When working with AI, treat it as a compiler that operates on data structures, algorithms, and architectural requirements rather than source code. You have to understand the theoretical pieces of what you're building before you instruct it to assemble them.
3. Use the AI as a powerful tool to grow your own knowledge of algorithms and troubleshooting. Whenever a problem crops up, it's an opportunity to come up with a few hypotheses of what the actual issue is. Don't let the model do it first. I have them actually write these down in our custom kanban tool as issue cards, and then they use the model to investigate how close they came to the true issue.
I'm hoping this will give them something similar to my experience of debugging over a lifetime of coding. The knowledge that seems to be most valuable that I bring to the table when coding with AI is in recognizing quality/maintainable code architectures, and "seen that before" debugging experience.
We just started this so I don't have much in the way of results yet, and it feels risky to even allow it into the curriculum. I don't think that it makes sense to hide from it though, so this is our best shot.
The real problem is that the environment for healthy learning is gone. At least when I was a kid, there's something magical about having an environment where nobody knows what the hell is going on and the learning is, to use your words "painfully slow". I guess we've been trained to think that way with all this modern technology, but back in the day, it didn't matter whether the final result was accomplished or not. All that mattered was the fun of trying to get something to work.
Nowadays AI shifts the emphasis to the final product, and frankly that's boring. Kids will use it because it's there, because it gives that initial result really quickly and we're hardwired for that. But it removes that cool environment of having a blank slate and just seeing things happen all on your own accord.
Companies might like AI for the short-term gains but we're doing the entire planet a disservice by having even invented AI, in my opinion. We're all being trained to be producers.
Can a person like you create a little microcosm of learning that can work? Maybe, but I get the feeling that programmers these days are being blinded by the fun of AI and forgetting that there's actually more to life satisfaction than having fun.
aethertap · · focus · HN ↗
So, I've changed my approach with my own teaching. I'm having them do three things that I'm hoping will prepare them to work in the world they're going to be entering soon:
1. Always have a handmade project going, and work on it without AI assistance even if it's painfully slow.
2. When working with AI, treat it as a compiler that operates on data structures, algorithms, and architectural requirements rather than source code. You have to understand the theoretical pieces of what you're building before you instruct it to assemble them.
3. Use the AI as a powerful tool to grow your own knowledge of algorithms and troubleshooting. Whenever a problem crops up, it's an opportunity to come up with a few hypotheses of what the actual issue is. Don't let the model do it first. I have them actually write these down in our custom kanban tool as issue cards, and then they use the model to investigate how close they came to the true issue.
I'm hoping this will give them something similar to my experience of debugging over a lifetime of coding. The knowledge that seems to be most valuable that I bring to the table when coding with AI is in recognizing quality/maintainable code architectures, and "seen that before" debugging experience.
We just started this so I don't have much in the way of results yet, and it feels risky to even allow it into the curriculum. I don't think that it makes sense to hide from it though, so this is our best shot.
vouaobrasil · · focus · HN ↗
Nowadays AI shifts the emphasis to the final product, and frankly that's boring. Kids will use it because it's there, because it gives that initial result really quickly and we're hardwired for that. But it removes that cool environment of having a blank slate and just seeing things happen all on your own accord.
Companies might like AI for the short-term gains but we're doing the entire planet a disservice by having even invented AI, in my opinion. We're all being trained to be producers.
Can a person like you create a little microcosm of learning that can work? Maybe, but I get the feeling that programmers these days are being blinded by the fun of AI and forgetting that there's actually more to life satisfaction than having fun.