The notion that Julia is not thoughtfully designed, and therefore we won't have the resources to make it run fast, is close to being the opposite of the main idea of the project. We don't want to go to extreme lengths to get performance, so we leverage design.
For example, one of the biggest challenges in dynamic type inference is getting the types of fields of mutable heap-allocated objects. We avoid this debacle by letting you declare field types, which also has benefits for code clarity and specifying memory layout. Everybody wins. But once you are writing types, you need fairly flexible types, to avoid being stuck with only Int and Any (everybody's favorites). We then follow the implications of this as far as we can.
As for "all those runtime type tag cases", the key is that they form a lattice, which feeds nicely into dataflow analysis. The lattice-theoretic properties of a language's universe of objects typically do not get enough attention, especially in dynamic languages, where it is actually most needed. Typically the lattices are either trivial (for example, scheme's fixed set of types), or highly uncooperative. You want to hit a sweet spot where you can compute greatest lower bounds that are actually somewhat interesting.
For example, one of the biggest challenges in dynamic type inference is getting the types of fields of mutable heap-allocated objects. We avoid this debacle by letting you declare field types, which also has benefits for code clarity and specifying memory layout. Everybody wins. But once you are writing types, you need fairly flexible types, to avoid being stuck with only Int and Any (everybody's favorites). We then follow the implications of this as far as we can.
As for "all those runtime type tag cases", the key is that they form a lattice, which feeds nicely into dataflow analysis. The lattice-theoretic properties of a language's universe of objects typically do not get enough attention, especially in dynamic languages, where it is actually most needed. Typically the lattices are either trivial (for example, scheme's fixed set of types), or highly uncooperative. You want to hit a sweet spot where you can compute greatest lower bounds that are actually somewhat interesting.