Maybe I have a fundamental misunderstanding, but I feel like hoping that model alignment and in-model guardrails are statistical preventions, ie you'll reduce the odds to some number of zeroes preceeding the 1. These things should literally never be able to happen, though. It's a fools errand to hope that you'll get to a model where there is no value in the input space that maps to <bad thing you really don't want>. Even if you "stack" models, having a safety-check model act on the output of your larger model, you're still just multiplying odds.