It is true that optional stopping won't change Bayes rule updates (which is easy enough to show). It's also true that optional stopping does affect frequentist tests (different sampling distributions). The broader question is "which behavior is better?"

p-hacking is when statisticians use optional stopping to make their results look more significant (by not reporting their stopping rule). As it turns out you in fact can "posterior hack" Bayesians - http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2374040

Edit: Also Debrah Mayo's Error Statistics book contains a demonstration that optional stopping can cause a Bayesian to construct confidence interval that never contain the true parameter value. Weirdly, those Bayesians can be posterior hacked even if you tell them about the stopping rule, because they don't think it matters.