An interesting aspect of Direct Instruction that I don't think has been pointed out yet (well, the book, written in 1982, might not be a likely place to find such a thought): this method of teaching seems ideally suited for teaching an Artificial Intelligence. Part of the gimmick of Direct Instruction is that it tries, as much as possible, not to make assumptions about what sort of things will be obvious to the learner. Granted, a lot of the internal structure still relies on experimental data gathered from human learners, but if we're creating an AI, it's a lot easier to program in a set of fundamental responses describing the way it should learn inductively, than to program in the concept of "red" or "faster than" by hand.

Yeah, I wasn't gonna mention this for ages, but the book Inferred Functions of Performance and Learning by Siegfried Engelmann and Donald Steely might contain some useful original ideas relevant to Artificial Intelligence, but I haven't read it myself and really have no idea beyond "sounds plausible".

(That is, I know I've been communicating very high certainty that DI is a very big deal when it comes to education, and I'm afraid some may have decided I have a general 'having very high certainty that things are big deals' trait, and thus misinterpret this recommendation as far stronger than it's intended.)

But Zig himself has a short description of what the book's supposed to be about here, so you might be able to come to a better conclusion yourself just by reading that.