>but then a layer of supervisors that are specialized on evaluating quality
Why would supervisor agents be any better than the original LLMs? Aren't they still prone to hallucinations and subject to the same limitations imposed by training data and model architecture?
It feels like it just adds another layer of complexity and says, "TODO: make this new supervisor layer magically solve the issue." But how, exactly? If we already know the secret sauce, why not bake it into the first layer from the start?
Similar to how human brains behave, it is easier to train a model to select a better solution between many choices than to check an individual solution for correctness [1], which is in turn an easier task to learn than writing a correct single solution in the first place.
[1] the diffs in logic can suggest good ideas that may have been missed in subsets of solutions.
Just add a CxO layer that monitors the supervisors! And the board of directors watches the CEO and the shareholders monitor the board of directors. It's agents all the way up!
LLMs are smarter in hindsight than going forward, sort of like humans! only they don't have such flexible self reflection loops so they tend to fall into local minima more easily.