Beyond Prompt and Response: A Case Study of Partially Formed Cognition and Human Judgment in Human–LLM Interaction

This paper examines a phenomenon observable in long-form human–large language model (LLM) interaction: the cognition that users bring into a dialogue does not always take the form of a fully formed question, an explicit proposition, or an answer that can be directly articulated. Sometimes, the user has only a vague but persistent sense of difference, a local relation, a directional judgment, or a sense that an existing formulation does not fit. Such partially formed cognition may not yet have found a stable articulation, but this does not mean that it lacks structure. The user may not yet know “what it is,” while already knowing “what it is not,” “which things need to remain related,” or “where the current formulation has gone wrong.” The paper takes as its primary case an extended human–LLM dialogue centered on the experience of reading Jane Austen. The dialogue does not begin with a problem that does not yet exist, but with a cognitive state that is not yet aligned: initially, the user has only a vague but persistent reading mismatch—“I don’t feel anything when I read Austen.” As the LLM offers different candidate representations, new comparisons, distinctions, and relational judgments gradually emerge. These include the juxtaposition of Austen and Eileen Chang, followed by a revised description of the user’s experience of reading Kafka and of the viewing position involved in that experience. The case suggests that human judgment can precede complete articulation. The user need not already possess the correct answer in order to recognize whether a candidate fits the relations previously sensed and to provide structured corrections. The role of the LLM in this process is closer to expanding local, low-resolution cognitive structure into candidate representations that can be subjected to further judgment. The paper also draws on recurring linguistic habits observed across the same user’s long-term interactions as supplementary material for examining how local relations, provisionality, and states of correction can become naturally externalized. The paper therefore offers a descriptive account of the phenomenon: some human–LLM interactions may involve more than an exchange between a problem and an answer. They may instead involve a cognitive state that already contains partial relational structure but is not yet sufficiently aligned, and that gradually acquires a more stable form of articulation through model expansion, human judgment, and structured correction. Such interactions make the boundary between “forming an answer” and “forming the problem itself” less clear, while also making human judgment an indispensable part of understanding this form of collaboration.