> These aren't chained, you can run parallel prompts of 15 personas with X diversity of perspective, that reason on a singular request, string, input or variabl

> These aren't chained, you can run parallel prompts of 15 personas with X diversity of perspective, that reason on a singular request, string, input or variable, they provide output plus audit explanation. You then run an amalgamation or committee decision (sort of like mixture of experts) on it to output variable or string. Then run parallel simulation or reflection prompts based on X different context personas to double check their application to outside cases, unconsidered context, etc. Sure, so you ensemble some results. You're back to the classical "hyperparameter" problem though that's faced ML for a long time-- what those personas are, what those subsequent prompts are, etc. require a fair amount of manual verification and tuning. And the search space is extremely vast. Not to mention that something like this is likely to be very unperformant.