It's just very conversational. If you are comfortable with stats and just need a reference it can be obnoxious. I think I went through the first edition in my PhD and it was better than a stats course. But when I want a quick reference for something it is to much reading to get to the point. It might be more well organized now though.

Statistical Rethinking is an immensely practical book, and probably the best book for anyone interested in the practice of statistics.

However, it is a bit too cautious about scaring readers away from the details of how things work. Honestly, I disagree with the parent that it's a bad book for the more mathematically inclined, since I can't think of any other book that gets you solving practical problems faster. But, if you have a strong math (or computational) background, you will be craving a deeper look under the hood.

ET Jaynes' Probability Theory: the Logic of Science is, imho, the best book for someone who wants to really understand the theory and reasoning behind statistics and is comfortable lots of mathematical thinking.

For a more practical (than Jaynes) but still more detailed book on statistics then I would recommend Bayesian Modeling and Computation in Python. Not quite as easy reading as Statistical Rethinking but there will be no mystery as to what's happening.