Compound specific stable isotope analysis of amino acids (CSIA-AA) is a practice that allows for in-depth studies of many different physiological, ecological, and environmental phenomena. The vast information obtainable through CSIA-AA has driven the exponential growth of this field since its mainstream introduction in the early 1990s. This growth, however, has been accompanied by the development of several distinct analytical approaches. Throughout this review, we outline the full CSIA-AA process and identify areas of its workflow with the highest potential to introduce measurement error. Through a meta-analysis of CSIA-AA publications, we found that rather than experimental application, the primary determinant of methodology lies in the geographic location of the analyst, likely reflective of the academic lineages of CSIA-AA practitioners as opposed to application specific method development. The relative nascency of amino acid isotope analysis gives it incredible expansion potential, but such expansion would greatly benefit from comprehensive experimentation optimizing every portion of the analytical process. While such optimization will require expertise across many areas (i.e., chemistry, mass spectrometry, and data science), uniform guidelines can ensure the highest achievable accuracy and precision for intra- and interlaboratory analyses, alike. The goal of this review is to improve data comparability and adopt standardized methodologies to uniformly generate highly accurate, precise, and reproducible data. In doing so, we make recommendations for areas that would benefit from further investigation (e.g., procedure optimization, error mitigation, and data handling methods). The creation and implementation of guidelines for optimal approaches to CSIA-AA - as has been done for applications like forensic science - can help realize the full potential of this rapidly growing field.