You can actually calculate exact gradients for spiking neurons using the adjoint method: https://arxiv.org/abs/2009.08378 (I'm the second author). In my PhD thesis I show how this can be extended to larger problems and more complicated and biologically plausible neuron models. I agree with the gist of your post though: Retrofitting back propagation (or the adjoint method for that matter) is the wrong approach. One should rather use these methods to optimise biologically plausible learning rules. The group of Wolfgang Maass has done exciting work in that direction (e.g. https://arxiv.org/abs/1803.09574, https://www.frontiersin.org/articles/10.3389/fnins.2019.0048..., https://igi-web.tugraz.at/PDF/256.pdf).