I wonder if you can combine the two - have a judge that examines both input and output. Perhaps this is one way to mitigate the alignment problem. The judge/supervisory LLM could be running on the same model / weights as the main LLM, but with a much more constrained objective - prevent the main LLM from behaving in undesirable ways either by moderating its input and even by halting the main LLM when undesirable behaviour is detected. Perhaps it could even monitor the main LLM's internal state, and periodically use that to update its own weights.