Comment by wegwerf17377382
1 day ago
So how do you build competence in a world where AI is preached to be the most reasonable way to solve problems because it's supposed to be faster than humans?
1 day ago
So how do you build competence in a world where AI is preached to be the most reasonable way to solve problems because it's supposed to be faster than humans?
The same way people have been doing so for years before ai. You may or may not remember, but the parent comment is basically a 1:1 copy of people complaining about how stack overflow provided young devs all the answers.
Some people took the answers and learned from them, incompetents just copy pasted them and called it a day.
The share of incompetence just went up significantly over the years, so its a lot more noticeable at this point.
Have a single human AI chef. Everyone else has to write an engineering statement and submit it to the AI chef. All that interaction is outside the codebase. Engineers will take turns - perhaps 1 month stints - being the AI chef.
I guarantee you'll spend less on tokens, have better documentation, better code, and most importantly more competent engineers.
I actually quite like this idea and might try something like it on my team because we're defacto heading in this direction anyway and everyone's a bit frustrated, might be better if it was acknowledged and made official as something to try.
On the other hand, I think this denies the reality (in my experience anyway but I think enough people will agree) that one often solves a problem as they are working on it.
This method seems to presume that a good engineer will submit a well thought-out solution or direction giving the AI an extremely good overview of each problem and enough of a description of what to do that it will do things as expected and they can just review the result.
In my experience it just doesn't work that way in practice. One learns the problem and even the domain while developing the solution. So one would have to submit at least a half developed solution not just "instructions", for there to even be coherent instructions in the first place. And one needs that experience working on the problem to be able to properly evaluate a separately proposed solution.
All in all for me this leads more towards using AI as a co-developer than using it to just implement some fully thought out idea and then check what it did.
That's like asking "how do you build competence in plowing a field with a horse in a world of tractors"
Pretty straight forward really, you keep using horses in parallel: https://www.abc.net.au/news/2025-10-18/heavy-horsemen-keep-f...
That's the other side of the country, but it's how it's done over here also.
Still pull the old plough varieties, still practice shed blacksmithing, etc - even while developing and using autonomous Ag-Bot tractors for spraying, etc.
The article you've linked paints it as life-style, entertainment - rich people hobbies, which is different than doing it because it's more productive.
People will "trad-code", but not because it's the productive thing to do.
2 replies →