Type coverage in Python improves readability, finds bugs and supports tooling to improve security and improve developer efficiency. However, driving for type adoption on a rapidly changing codebase under active development can pose several challenges. This presentation will focus on how you can get meaningful results from Pyre as you move from just a few annotations to a fully typed codebase, and the guarantees we can make along the way. Then, I will discuss the approaches and tools we use to increase type coverage and “strictify” the Instagram codebase, one of the largest active Python projects.