"Evolution is a tinkerer, not an engineer. It works with what is already there and takes the path of least resistance.
It is not always the most efficient solution, but it is the dumbest solution that works."
-François Jacob, "The Logic of Life: A History of Heredity"
Reverse engineering complex systems is a tricky problem. Look for example at the design of modern microprocessors, how easy it would be to see the underlying principle of the Turing machine behind all the caches, branch prediction, thread balancing, and the rest. Not that easy I would say. This example might be also applicable to reverse engineering the mind. After peeling out all the evolutionary optimisations the underlying principles of brain design might turn out modestly simple. Some of these optimisations have been already identified and well studied[1] (e.g. mechanisms of translating chemical signals to electrical ones, numerous structural decisions dedicated to spending as less wire and energy as possible, ways of getting information from different sensors to the same frequency). While we have not yet succeeded in this quest the idea of simple but powerful core principles should be part of our strategy of getting there.
Biology offers one more piece of the strategy. Although the overall amount of “design work” done by evolution is incredible, only a fraction of it is directly associated with the decision-making circuitry of the mind. The relatively slow pace of cognitive evolution means that there was not much time for reinventing cognitive architecture between subsequent species. Meaning, the most necessary parts of the apparatus have been already present in primates, some smaller part has been present in mammals, and so on.
The reasoning above together with a liberal application of the Lindy Effect[2] justify us taking a certain stance towards reverse engineering the mind - the longer some specific design principle has been around, the more it got represented in the construction of the system and the more we should put emphasis on it while building our models.
By this logic, we should expect the bulk of the design to be implemented via the use of a tiny set of the oldest mechanisms (if we take into account the timeframes of the introduction of all of them). The prime suspects for that set are:
Principles of Neural Design. Peter Sterling and Simon Laughlin. https://mitpress.mit.edu/9780262534680/principles-of-neural-design/