This article is the first in a series dedicated to the content of the book Causal Inference: The Mixtape, in which I will try to summarize the main topics and methodologies exposed in the book. DAGs (Directed Acyclic Graphs) are a type of visualization that has multiple applications, one of which is the modeling of causal relationships. We can use DAGs to represent the causal relationships that we believe exist between the variables of interest.