The European Research Council-funded project “STEMMA: Systems of Transmitting Early Modern Manuscript Verse, 1475 to 1700” computationally models the manuscript circulation of early modern poetry to gain macro-level insights into the overlapping contexts in which it was written, read, and copied. To facilitate STEMMA’s ultimate goal of modeling the circulation of manuscript poetry as a large-scale network, the project began by combining and reconciling five of the most authoritative sources of relevant data using staged large language model (LLM)-assisted pipelines. These pipelines were effective on a large proportion of the data, but they struggled in relation to particular features of early modern poetics, including imitation, translation, and unique works. This article considers how general models’ shortcomings in relation to early modern poetry can be considered a feature rather than a bug, pointing up new insights into poetics by defamiliarizing them. It considers productive intersections between literary theory and criticism and recent scholarship on LLMs and suggests that two seemingly very different fields of study address what are, at core, rather similar fundamental questions.