Sure, not 100% unique to academia, there are also industrial research environments.

My phd was in physics, and there were lots of examples. Weird tricks for aligning optics benches, semi-classical models that gave good order of magnitude estimates despite a lack of rigour, which estimates from the literature were trust worthy (and which estimates were garbage). Biophysics labs and material science lab all sorts of rituals around sample and culture growth and preparation. Many were voodoo, but there were good reasons for a lot of them as well.

Even tricks for using equipment- such and such piece of equipment might need really good impedance matching at one connection, but you could get by being sloppy on other connections because of reasons A, B and C,etc.

A friend of mine in math was stuck trying to prove a lemma for several months when famous professor Y suggested to him that famous professor Z had probably proven it but never bothered to publish.

Jason Mitchell writes in "On the emptiness of failed replications" that there certain knowledge you need to replicate experiments that's not in the paper:

I have a particular cookbook that I love, and even though I follow the recipes as closely as I can, the food somehow never quite looks as good as it does in the photos. Does this mean that the recipes are deficient, perhaps even that the authors have misrepresented the quality of their food? Or could it be that there is more to great cooking than simply following a recipe? I do wish the authors would specify how many millimeters constitutes a “thinly” sliced onion, or the maximum torque allowed when “fluffing” rice, or even just the acceptable range in degrees Fahrenheit for “medium” heat. They don’t, because they assume that I share tacit knowledge of certain culinary conventions and techniques;

[...]

Likewise, there is more to being a successful experimenter than merely following what’s printed in a method section. Experimenters develop a sense, honed over many years, of how to use a method successfully. Much of this knowledge is implicit. Collecting meaningful neuroimaging data, for example, requires that participants remain near-motionless during scanning, and thus in my lab, we go through great lengths to encourage participants to keep still. We whine about how we will have spent a lot of money for nothing if they move, we plead with them not to sneeze or cough or wiggle their foot while in the scanner, and we deliver frequent pep talks and reminders throughout the session.

How best to give those pep talks would be an example.