Can OLS VIF be used as a diagnostic for multicollinearity before fitting a Bayesian regression?

My assumption has always been that VIF is measuring redundancy in the predictors, a property of the design matrix that exists before any estimation method is applied. On that basis, I’ve used OLS + VIF as a quick pre-diagnostic before fitting Bayesian regressions (Gaussian likelihood, weakly informative priors).

I’ve recently been publicly challenged for doing this, with the argument that VIF is “frequentist-specific”, frequentist diagnostics do not carry over, and that Bayesian regression suffers more from multicollinearity than OLS.

Questions:

1. Is it valid to use OLS + VIF as a pre-diagnostic when the ultimate model is Bayesian?
2. If not, what are better Bayesian-native ways to detect or handle multicollinearity?

Any authoritative references or examples comparing how multicollinearity manifests in OLS vs Bayesian regression would be very useful.