The Julia programming language was designed around a lofty objective: to let scientists and researchers write both dynamic scripts and fast libraries in the same language while also facilitating decoupling and abstraction. Moreover, Julia wanted to do this with a scrappy academic development team of three people and in the span of about two years. I’ll talk about the decisions that Julia made early on to meet this goal, reflect on how those decisions have aged as the language (and ecosystem around it) matured, and about some key lessons that other languages might be able to learn from Julia’s experience.