Crucially, does it make capabilities infinitely scalable? My comment just said that models may have a hard cap, and maybe doing specific setups like yours can make reaching it easier, but making the 'team' 10x larger after that optimal point may bring few to no improvements.

Although I'm also not sure about just how much better models can really get with this technique. Ultimately you're still getting the same model with the same training data, which are the important parts. Asking it to pretend to be something feels like it would just put a color filter in front of the conclusion the model has already predicted, or maybe alter the path to the conclusion slightly or pick a less likely answer that it still could've provided normally.