I don't agree with this! In reality we don't get asymptotic properties, we get finite sample properties, and these can vary greatly. E.g. MLE often won't even converge for hierarchical models without a fair amount of data. Also, for bespoke models there often isn't a published frequentist estimator available, and attempting to derive one would be a much bigger issue for most people than the computational resources required for MCMC or variational inference.
> and you usually get the same answer anyways
I don't agree with this! In reality we don't get asymptotic properties, we get finite sample properties, and these can vary greatly. E.g. MLE often won't even converge for hierarchical models without a fair amount of data. Also, for bespoke models there often isn't a published frequentist estimator available, and attempting to derive one would be a much bigger issue for most people than the computational resources required for MCMC or variational inference.