Eventually it clicked when considering the Discrete Fourier transform [3], which is just an orthogonal matrix you multiply onto a vector. All the stuff about the inverse FFT, Plancherel theorem and Parseval's theorem come for free: they just say that the matrix is orthonormal.
Maybe this only works if you've already invested in understanding linear algebra. But once I had this discrete understanding, back porting it to the continuous Fourier transform was easy enough.
Maybe I'm weird, but this was a case where just looking at the equations was much easier than all the animations of circles and stuff.
[1] https://www.youtube.com/watch?v=spUNpyF58BY
[2] https://betterexplained.com/articles/an-interactive-guide-to...
[3] https://en.wikipedia.org/wiki/Discrete_Fourier_transform