Probability is highly non-intuitive (kind of like quantum mechanics), so most people (including scientists) don't understand it and just memorize "protocols" and "formulas" and "p-value stuff".
https://www.tandfonline.com/doi/full/10.1080/00031305.2018.1...
Science is messy but eventually consistent. Everybody should be cautious of single results and instead rely on the community to synthesize those results into predictive models.
We've learned not to value developers based on lines of code written, and to value refactoring and elimination of code, scientist can also do the equivalent. Scrutinize, weed out, reinterpret old things, mentor others, etc. Much stuff beyond finding p<0.05.
But such things are rather seen a side quests, secondary purposes, almost like a hobby (e.g. writing a textbook).
I do find it ironic though that this is so difficult to explain that I apparently have to read a paper to understand it... I would've thought the blog post was trying to explain things in simple terms...