I love my rabbit holes, but at work, it's often not viable to explore them given deadlines and other constraints. If you want your wheel to be used in production though, it better be a good wheel, better than the existing products.
Chesterton himself was using it as a religious metaphor, and I think most of us agree that software engineers are not literal gods.
Also, in software, you may find the fence sometimes exists in higher dimensions than the usual three, can turn invisible for part of its length, and occasionally exists but is four inches tall and blocks only mice. And it may also be designed, at least in part, by a blind idiot god called ChatGPT on whose altar consciousness itself is sacrificed. At this point it's worth considering whether keeping the fence around is worse than letting the bull out.
Of course mismanagement happens but the implied value of understanding why the fence was erected is to understand the expected value it would bring and understand the problem it was trying to solve. This does not imply that it should have been erected, just that there were others before you trying to solve a problem and if they're failing it's important to know why so you don't fail in the same way.
But it was also low-value data and even in the worst case we surmised the most we'd do is anger someone in marketing briefly.
I think so long as you can ascertain that the stakes are low, this is a good tactic.
True for life in general. We have limited lifespans. Aging and death really are the great grand daddy of all problems.
Same can be said of learning a large inherited codebase. If you're assigned to a large piece of functionality and you need to understand it, your first instinct shouldn't be to rewrite the whole thing from scratch just to understand it; it should be to either read the code and documentation, or if those are impossible to comprehend, ask around what it's supposed to do, maybe even write tests to get a general sense of the behavior.
I don't expect programmers to be cognitive psychologists here but the thing about learning is that you must do a "progressive overload" of complexity as you go, which is why building on top of what exists is the best way to go. You get a general idea first of what something is supposed to do, and then when you're good enough, that's when you can work backwards to building something from scratch where all the complexity at lower levels of abstraction wouldn't be too much for your brain to handle. Starting with a large amount of complexity will impair your learning and only discourage you.
Personally, I’m a fan of learning by doing. Reinventing the wheel works better for me than just about anything I’ve tried.
The expense (time or otherwise) follows from how intimately you have to get to know the subject. Which is precisely why it's the best way to learn. It's not always viable, but when you can spare the expense nothing else compares.