The part about entropy encoding only seems explain run-length encoding (RLE). Isn't the interesting aspect of making use of entropy in compression rather to rep

The part about entropy encoding only seems explain run-length encoding (RLE). Isn't the interesting aspect of making use of entropy in compression rather to represent rarer events with longer longer code strings? The fair coin flip is also an example of a process that cannot be compressed well at all because (1) the probably of the same event happening in a row is not as high as for unfair coins (RLE is minimally effective) and (2) the uniform distribution has maximal entropy, so there is no advantage in using different code lengths to represent the events. (Since the process has a binary outcome, there is also nothing to gain in terms of code lengths for unfair coins.)