The development of standardized, high-quality benchmarks is crucial to the continual advance of scientific methods. In atomistic simulation, benchmarking drives the development of new density functionals, basis sets, & corrections and allows researchers to assess the accuracy of new machine-learning-based approaches. Following the oft-cited adage that "you get what you screen for," 1 ensuring that good benchmarks exist for all desired applications of atomistic simulation is key to driving rigorous and systematic progress in computational chemistry.