It is common wisdom that people should be given tasks that computers can’t do well, and computers should be given tasks that people can’t do well. So in design computing why are we attempting to study computational design creativity? The main answer is that the field (like many others) progresses by tackling simpler problems first and moving towards harder ones. Routine parametric design and design checking were starting points, moving gradually to Configuration and most recently to harder problems such as distributed/collaborative design and to creative design: moving from routine to non-routine [Brown 1996]. One goal has always been to build working systems, while another is to learn more about the knowledge and reasoning used for each type of design activity studied. Computational design creativity is hard to study, and until fairly recently it has received very little attention, even though it is widely held to be very important both from intellectual and economic points of view. It has mostly been studied by looking at analogical reasoning and genetic algorithms: i.e., the focus has been on extreme non-routine cases. There are hard sub-problems and other ways of moving towards creative systems that are worth considering. This paper suggests an alternative approach to computational design creativity research that might be labeled “routine creativity”.