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Short abstract

This methodographic story explores the co-composition of a book chapter with Large Language Models. By focusing on how visualisation choices emerge in distributed reasoning, it reframes generative AI as a partially tamed co-constituent, foregrounding epistemic, technological & ethical entanglements.

Long abstract

The rise of genAI invites a rethinking of how STS scholars study and account for distributed intelligences in contemporary research and writing practices. I critically examine the performative entanglements that arise when co-composing academic texts with Large Language Models (LLMs). Anchored in methodographic practice (Lippert&Mewes 2021) and a Baradian diffractive analytical sensibility, I reconstruct the making of a collaboratively co-composed book chapter, elaborating on how epistemic-onto-performative effects emerge in text creation when distributed across human-LLM interactions.

Focusing specifically on the negotiation of visualisation choices—aimed at illustrating analytical distinctions within the chapter—I explore how interpretive, methodological, and epistemic commitments manifest through interactions with GPT, including the co-analysis of Python code used to transform hand-drawn sketches into graphics. This inquiry reveals how reasoning is enacted as a co-constitutive and iterative process with ambiguously bordered agencies spanning human cognition, language model affordances, and platform infrastructures. Specifically, it attends to the generative tensions that arise when deploying LLMs simultaneously as epistemic tools, media-logical actors, and objects of reflective inquiry.

Ultimately, this methodographic vignette contributes to reframing generative AI from being either merely instrumental or destructive, towards becoming a partially tamed co-constitutive in a method assemblage. By centering on how reasoning itself is distributed—in terms of visualisation, language, and distinction-making—this work foregrounds the underexplored intersections of empirical philosophy, technological mediation, and responsibility. It invites STS scholars to consider not just how methods are made with genAI but also how these entangled practices are implicated in the production of situated knowledge, accountability, and socio-material worlding.