The specific method outlined here seems pretty doable by today's models, which don't seem smart enough to have some kind of 4d chess hidden alignment.

You just have to go through a ton of all of a model's neurons and identify the associated motif, then use that model as a research model to figure out how to tune out bad behavior.

It's pretty hard to imagine today's models subtly recognizing a motif for bad behavior in the research model and then lying about it. Or lying about the results of an alignment training run. It's possible, I guess, but it seems unlikely, and I don't really think there's any evidence of current models having that variety of misalignment.