> 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

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oytis 14 hours ago | parent [-]

I don't know where it goes, but it sounds pretty dumb for the companies involved too. Tech companies are in the business of nurturing teams knowledgeable in things so they can build something that gives them an advantage over competition. If there is no knowledge being built, there is no advantage and no tech business.

	▲	hobofan 14 hours ago \| parent [-]
		> Tech companies are in the business of nurturing teams knowledgeable in things It pains the anti-capitalist fibers in my body to say this, but no they are not. At the maximum the value is in organizational knowledge and existing assets (= source code, documentation), so that people with the least knowledge possible can make changes. In software companies in general, technical excellence and knowledge is not strongly correlated with economic success as long as you clear a certain bar (that's not that high). In comparison, in hardware/engineering companies, that's a lot more correlated. In the concrete example of a legacy codebase we have here, there is even less value in trying to build up knowledge in the company, as it has already been decided that the system is to be discarded anyways.