Daisaku Sato | Searcharxiv

arXiv2026

Vibe to Code: Elucidating Strategic Oscillation of Tacit Knowledge in Generative AI Design Workflows -- An Exploratory Qualitative Study

The rapid adoption of generative AI tools has created new literacy demands for designers who must verbalize tacit knowledge through natural language prompts. Yet the micro-level cognitive processes by which designers externalize implicit intentions during iterative AI dialogue remain underexplored. This exploratory qualitative study examined five expert designers (11-20 years UI/UX experience, M = 15.4 years) using think-aloud protocols. We identified "Strategic Oscillation" -- experts' intentional return to vague language (Vibe) after progressing toward operational specifications (Code), leveraging AI's probabilistic nature for creative exploration. We observed shifts from "instruction" to "consultation" mode, deep reflection triggered by semantic collisions, and one participant's disengagement revealing conceptual alignment as a tentative boundary condition. We propose the ECRT cycle (Expectation-Collision-Reflection-Transformation) operationalizing the SECI model's "externalization" phase for human-AI collaboration. These findings yield three design patterns for metacognitive support and position AI as a "probabilistic mirror" catalyzing tacit knowledge externalization.

cs.HC↗

arXiv2026

Repair as Representational Work: Integration Bottlenecks in AI-Assisted Development

Research on AI-assisted programming has concentrated on the gulf of execution -- how users write successful prompts. We report a candidate phenomenon, an integration bottleneck, that lies in Norman's gulf of evaluation: a repair-relevant contribution reaches the user and fails to become actionable at the point of receipt. Two cases in an eighteen-case corpus of publicly shared AI-assisted-development accounts report this, from a peer and from the system's own output; both fall at evaluation's interpretation stage, and a third, which would fall at comparison, is reached only on an inferential reading and reported as a boundary case. A within-case contrast is consistent with actionability turning on whether the contribution can be restated as an instruction without an intervening judgement. We report this as a candidate warranting dedicated study, not an established regularity; its evidence base is retrospective author self-reports. On the submission side, medium alone did not sort the corpus contrasts; immediate uptake aligned with a checkable condition across four decisive contrasts, while a fifth case shows checkability sufficient for immediate uptake did not guarantee persistence. A twenty-trial multi-turn probe across two current models observed no constraint loss in fifteen judgeable narrow trials, and a ten-trial extension with an explicit restructuring request none in eight. Study 2 is not a replication attempt: it isolates regeneration, the mechanism the corpus authors invoke, and removes it as a sufficient explanation. We specify four interaction requirements for an accepted-constraint ledger; a conformance analysis of twelve mechanisms found none documented to satisfy all four.

cs.HC↗