alt Hacker News> I have stopped writing code, occasionally I jump into the changes proposed by LLM and make manual edits if it is feasible, otherwise I revert changes and ask it to generate again but based on my learnings from the past rejected output
Isn't it a very inefficient way to learn things? Like, normally, you would learn how things work and then write the code, refining your knowledge while you are writing. Now you don't learn anything in advance, and only do so reluctantly when things break? In the end there is a codebase that no one knows how it works.
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> you would learn how things work and then write the code
In a legacy codebase this may require learning a lot of things about how things work just to make small changes, which may be much less efficient.
> Isn't it a very inefficient way to learn things?
It is. But there are 2 things:
1. Do I want to learn that? (if I am coming back to this topic again in 5 months, knowledge accumulates, but there is a temptation to finish the thing quickly, because it is so boring to swim in huge legacy codebase)
2. How long it takes to grasp it and implement the solution? If I can complete it with AI in 2 days vs on my own in 2 weeks, I probably do not want to spend too much time on this thing
as I mentioned in other comments, this is exactly makes me worried about future of the work I will be doing, because there is no attachment to the product in my brain, no mental models being built, no muscles trained, it feels someone else's "work", because it explores the code, it writes the code. I just judge it when I get a task