You don't need to understand all the stuff you use.
How complex it is is not relevant unless it has a tangible impact.
eg. I use spark a lot. I don't really deeply understand how the DAG is translated into a distributed computation and the results are aggregated from the cluster.
It calculates things. It's fast. Sometimes I'm surprised by things that are slower than I expect. Oh well. Don't do lots of column renames. /shrug
It's a tradeoff.
Is the effort to understand the detail worth the benefit of doing so? Does not understanding it cause enough pain that it become prohibitive to develop using it?
Is it for spark? No. I really don't care how it's implemented. I don't even know scala. It works fine.
Is it for assembly? No. I don't care at all how my code is JIT'd to assembly / code. It just works.
It it for react hooks? I honestly haven't personally found it to be... but I don't write custom hooks much.
So, your experience with hooks might be different, and you may find the trade-off is more expensive if your case, because it tangibly causes, eg. bugs when you write your code.
...but you are quite wrong if you think that not understanding how something works is a fundamental obstacle to using it.
That is categorically false.
I would argue that it's far from proven that using complex systems necessarily causes the complexity of your system to balloon out of control... or that there is even a strong casual relationship between "mental model being complex to grasp" and the resulting complexity of the system.
> ...it's far from proven that using complex systems necessarily causes the complexity of your system to balloon...
I don't know what "proven" would actually mean in this context, but there's a notion called "leaky abstraction". It bites you hard when you use a "do-everything" framework and something goes wrong.
All of sudden, the magic stops and you have to deal with a ream of obtuse stack traces, problems that completely smash your metal model of what's going on, and you end up in deep rabbit holes of stuff you don't want to get into at the worst possible time. That is a fundamental obstacle.
All things given, I'd rather use a tool that does not have leaky abstractions and if I need to investigate the inner workings of an abstraction, I can form a mental model of that abstraction with little effort. To your point, you don't need to understand the inner workings of your tools, but being able to quickly learn about the inner workings of the tools is beneficial to creating abstractions, crafting solutions, fixing issues, performing refactoring, tracking the usage of concepts across the codebase, etc.
Thats the point: the mental model is irrelevant unless it causes bugs when you use it wrong.
Does it? Does it actually cause bugs?
Not, “in general”; You’re just doing the same thing again here and doing vague hand waving. What actual bugs? What types of bugs?
Be specific
(yes, it does cause bugs, but see how this conversation is pointless when you don’t provide any details? Right, now go read the first post in this thread.)
How complex it is is not relevant unless it has a tangible impact.
eg. I use spark a lot. I don't really deeply understand how the DAG is translated into a distributed computation and the results are aggregated from the cluster.
It calculates things. It's fast. Sometimes I'm surprised by things that are slower than I expect. Oh well. Don't do lots of column renames. /shrug
It's a tradeoff.
Is the effort to understand the detail worth the benefit of doing so? Does not understanding it cause enough pain that it become prohibitive to develop using it?
Is it for spark? No. I really don't care how it's implemented. I don't even know scala. It works fine.
Is it for assembly? No. I don't care at all how my code is JIT'd to assembly / code. It just works.
It it for react hooks? I honestly haven't personally found it to be... but I don't write custom hooks much.
So, your experience with hooks might be different, and you may find the trade-off is more expensive if your case, because it tangibly causes, eg. bugs when you write your code.
...but you are quite wrong if you think that not understanding how something works is a fundamental obstacle to using it.
That is categorically false.
I would argue that it's far from proven that using complex systems necessarily causes the complexity of your system to balloon out of control... or that there is even a strong casual relationship between "mental model being complex to grasp" and the resulting complexity of the system.