Beyond the Answer Engine: A Triangulation Interaction Grammar for Auditable Knowledge Production in Human-AI Systems

Recent advances in Large Language Models have shifted human-computer interaction toward conversational fluency, but existing frameworks often conflate rhetorical elegance with epistemic validity—a vulnerability termed The Fluency Trap. This white paper argues that the central bottleneck for rigorous AI-assisted reasoning is the absence of a structured interaction grammar, and it formalizes knowledge production through four criteria: traceable evidence, independent rival hypotheses, discriminative empirical falsifiability, and an auditable reasoning path. To address this gap, the paper introduces the Triangulation Interaction Grammar (v1.0), a state-bound, asynchronous architecture grounded in the functional triad of Builder, Critic, and Sovereign Human Steward, with two decoupled workspaces and six sovereign exit terminals under non-delegable human liability. The paper also specifies, in advance of empirical testing, the falsification criteria under which the grammar’s structural utility hypothesis must be rejected; no empirical validation is reported in this document.