This is missing the most important thing which is why HRs are so damn useful. It's because (a) survival analysis is very statistically powerful, but (b) many survival curves do not follow a very well-described parametric function. The genius of David Cox was in realizing that, when proportional hazards hold, you can just cancel out the unknown survival function and get the multiplicative hazard ratio immediately, in a statistically powerful and statistically efficient manner. Extremely useful if you are, say, trialing a novel chemotherapy drug and want to end your trial ASAP to get everyone on the intervention arm if the drug actually works.

The places where proportional hazards gets squirrely (very long observation times, crossing curves) are a small fraction of the use cases of survival analysis, and dunking on them for "not being Bayesian" or whatever misses this broader context.