This is the first in a series of articles exploring knowledge representation in Artificial Intelligence from the perspective of a practical implementer and programmer. AI is now a collection of approaches that has seen practical commercial application in search, linguistics, reasoning and analytics in a wide variety of industries. How we represent knowledge in a computer affects how our applications perform, which algorithms we choose, and in fact whether the applications can be successful. Graphs have long been a popular mechanism in AI for encoding knowledge about the world. In their simplest form there are just nodes and arcs and each can have labels.