The steelman of this argument would be something like "experimentally, we find that investigators who take experimental approaches tend to do better than those who take theoretical approaches". But first, this isn't obviously true... mathematicians, for instance, have found theoretical approaches to be more powerful. (I'd guess that the developer of Bitcoin took a theoretical rather than an empirical approach to creating a secure cryptocurrency, for instance.)

This example actually proves the opposite. Bitcoin was described in a white paper that wasn't very impressive by academic crypto standards - few if anyone became interested in Bitcoin from first reading the paper in the early days. It's success was proven by experimentation, not pure theoretical investigation.

My impression is that MIRI thinks most possible AGI architectures wouldn't meet its standards for safety, so given that their ideal architecture is so safety-constrained, they're focused on developing the safety stuff first before working on constructing thought models etc. This seems like a pretty reasonable approach for an organization with limited resources, if it is in fact MIRI's approach. But I could believe that value could be added by looking at lots of budding AGI architectures and trying to figure out how one might make them safer on the margin.

It's hard to investigate safety if one doesn't know the general shape that AGI will finally take. MIRI has focused on a narrow subset of AGI space - namely transparent math/logic based AGI. Unfortunately it is becoming increasingly clear that the Connectionists were more or less absolutely right in just about every respect . AGI will likely take the form of massive brain-like general purpose ANNs. Most of MIRI's research thus doesn't even apply to the most likely AGI candidate architecture.