Understanding how people explain is a core task for cognitive science. In this opinion article, we argue that research on explanation would benefit from more engagement with how the cognitive systems involved in generating explanations (e.g., attention, long-term memory) shape the outputs of this process. Although it is clear that these systems do shape explanation, surprisingly little research has investigated how they might do so. We outline the proposed mechanistic approach to explanation and illustrate it with an example: the recent research that suggests explanations exhibit a bias toward inherent information. Taking advantage of what we know about the operating parameters of the human mind is likely to yield new insights into how people come up with explanations.