There has been an increasing interest within the Material Science community to use Automatic Differentiation (AD) tools for deriving and calibrating constitutive models. AD tools usually focus on being black-box and comprehensive, while in Continuum Mechanics, the user needs to interacts with the derivative of various pieces, since those derivatives are interpretable and essential to solving forward and inverse problems. Thus, we aim to investigate the challenges one might encounter in using AD tools in Continuum Mechanics workflows. In doing so, we specifically use Enzyme-AD in Ratel, a new, open-source package capable of solving complex solid mechanics problems on various computing devices without sacrificing computational performance. Ratel supports several material models, including Hyperelasticity and plasticity. In this study, we reproduce our hand-coded models with Enzyme-AD and compare the performance and difficulty of two approaches.