“Literate programming” is an approach to writing software programs that weaves together the source code and documentation at the time of creation. The idea is to create programs that are easier for users to understand. But they are also easier for programmers to work on and maintain. In this talk, I will describe how data scientists can be inspired by this programming approach and start what I refer to as “literate projecting.” Literate projects are not only more pleasant to work on — they are also easier for others to discover and explore. In my experiences as a researcher and now a data scientist at RStudio, I’ve had the pleasure to work on many literate projects, and I’ve felt the pain of working on illiterate ones too. What is the difference? What are the benefits? Based on my experiences, I’ll share good literate projecting practices that have the potential to shift your mindset and reshape your workflow.