They're different kinds of easy...

Writing fresh code is easy because you just express your ideas. What's hard is hitting all the contingencies appropriately; it can take years of 'burn in' to get right.

Reading code is easy - especially if you don't know the language well - because someone has already assembled all the correct syntax, etc. What's hard is that the code may be convoluted from years of monkey-patches to handle all those inconvenient contingencies, to the point of obscuring the core ideas. eg, making you search through ten nested indirections to figure out how something actually executes...

On the writing side, LLM's make it much easier to have the idiomatics of the language easily on hand. (eg, I never ever remember the exact way to use 'super' in python... but ML assistance is happy to fill in the parens as soon as I start them.)

Not really, reading existing code is hard because you have to be on guard that your bias isn’t skewing your judgement about what’s going on.

What I’m getting from these comments is (as expected), most people are happy to take the easy assumption filled route rather than actually applying rigour.

My co-researcher was thrown in with the sharks on that project. He'd never even taken calculus, let alone any form of coding class. And this was Matlab, by the by, a language that not only holds your hand, but chews your food for you too. He never really groked matrices either.

We were a neuro lab, so coding was seen as something similar to a hammer: Bang away with it all you want, but at the end of the day, it's going back in a dark drawer where it belongs with the other tools.