fwiw I’ve been writing code for 2 years and I have occasionally benefitted from half-remembering the concepts that big O notation describes (even though my memo

fwiw I’ve been writing code for 2 years and I have occasionally benefitted from half-remembering the concepts that big O notation describes (even though my memory of the proper terminology is pretty shoddy, it’s been a long time since we covered it in college) When new releases of website features have resulted in notably poor performance, and profiling has revealed a particular function taking time on the order of seconds to complete (seconds are an eternity in UI land) it’s important to be able to reach into code that processes big chunks of data, and identify loops-within-loops-within-loops that could be rearchitected to play out more efficiently. Knowing that you’re going from O(n^2) to O(2n) is really just a matter of jargon - knowing that your list of results now displays in 1/10th the time, and why, is still pretty important. The underlying logic/math is the important bit to have a concept of, imo, big O is just a fun way to talking about it.