Tensor network methods are an extremely useful class of simulation algorithms in physics. They work by constructing a graph of tensors -- of which matrices and vectors are low-dimensional examples -- and making local optimizations to these tensors to capture the essential physics of a many-body system. ITensor (Intelligent Tensor) is a leading C++ package created to make tensor network methods accessible to a wider group of scientists and programmers. In this talk, we present ITensors.jl, a ground-up rewrite of ITensor in Julia, which uses the lessons from the C++ project to offer much of the same powerful functionality in a more concise and elegant format, substantially lowering the "barrier to entry" for using tensor network techniques. We will present some usage examples that are common in physics applications to exemplify the ITensors.jl user interface and design philosophy. Using Julia, we can create a tensor network package expressive enough to capture a variety of physics that's also accessible enough for more physicists and computer scientists to use.