It is still unclear how an evolutionary algorithm (EA) searches a fitness landscape, and on what fitness landscapes a particular EA will do well. The validity of the building-block hypothesis, a major tenet of traditional genetic algorithm theory, remains controversial despite its continued use to justify claims about EAs. This paper outlines a research program to begin to answer some of these open questions, by extending the work done in the royal road project. The short-term goal is to find a simple class of functions which the simple genetic algorithm optimizes better than other optimization methods, such as hillclimbers. A dialectical heuristic for searching for such a class is introduced. As an example of using the heuristic, the simple genetic algorithm is compared with a set of hillclimbers on a simple subset of the hyperplane-defined functions, the pothole functions.