I tend to be of the mindset that over the long term, you are going to get a good perspective if you approach the problem 50/50. Apply randomness half the time, apply the knowledge you know the other half. Divide and conquer, sort of.

Randomness potentiates the space that you will both be able to identify error and consequently, find mistakes, find errors in reasoning (Monte Carlo simulations are traditionally used for this sort of thing). The other good thing with randomness as well, find ways to see errors as being 'not errors', e.g. a tool that can be developed, structured, a new way to see the problem, a creative approach. Some melding between the two seems to be something of significance for an AI. So you don't want it to be all random, because you need stability, structure, you need a 'language' or an 'awareness' you understand that isn't so chaotic and constantly changing that you can't even find a place to put your feet on the ground.

It doesn't have to be a perfect 50/50 balance, because that has it's own set of problems - divide and conquer all the divisions and you still wind up with 2^n newly defined problem spaces to interpret, possibly losing sight of the bigger picture or maintaining independent direction in one focused lineage of all those spaces. Just very generally, maintain balance, because the world is chaos sometimes.

It's like a stream of information. All the analysis to all of that space is meaningless if the context changes enough. So, adapt to a new context.

Honestly though, I don't know what I'm trying to say much of the time, aside, 'help', lol. Life is terrifying. :)