Vibe Compiler: A Research-Logic Synthesis Tool That Runs without Prompt Engineering -Toward Enhancing Metacognition for Sustaining Agency in the Age of Generative AI-

• URL: http://arxiv.org/abs/2608.05545v1
• Date: Thu, 06 Aug 2026 02:51:03 GMT
• Title: Vibe Compiler: A Research-Logic Synthesis Tool That Runs without Prompt Engineering -Toward Enhancing Metacognition for Sustaining Agency in the Age of Generative AI-
• Abstract summary: We present the Vibe Compiler, a research-logic compiler that helps researchers transform vague ideas into coherent research logic.<n>The framework characterizes structural gaps along two dimensions: cognitive function (Synthesis vs. Analysis) and executing agent (human vs. AI)
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Generative AI used as a capable servant has greatly accelerated intellectual work, but it also risks eroding human epistemic agency by encouraging uncritical acceptance of AI-generated reasoning. This creates a need for mechanisms that preserve human agency by augmenting metacognition during AI-assisted intellectual work. To address this, we propose the Synthesis-Analysis Reciprocity Model, which views intellectual construction as a reciprocal interaction between Synthesis, which combines components into an artifact, and Analysis, which critically evaluates them against objective indicators and constrains subsequent synthesis. Grounded in this model, we present the Vibe Compiler, a research-logic compiler that helps researchers transform vague ideas (Vibes) into coherent research logic. The system compiles these ideas using a research paper ontology of sixteen academic parameters. Compilation failures indicate missing logical components; rather than filling them autonomously, the system prompts researchers with reflective questions that encourage them to develop the missing reasoning. The framework characterizes structural gaps along two dimensions: cognitive function (Synthesis vs. Analysis) and executing agent (human vs. AI), yielding four origin types that identify where breakdowns arise. Our design emphasizes AI probing its own synthesized output to stimulate human metacognition, encouraging researchers to remain managers who critically direct and validate AI-generated reasoning rather than passive recipients. Experience with a prototype built on NotebookLM and Gemini suggests that effective AI-assisted reasoning depends less on sophisticated prompting than on the knowledge structure provided to the AI. This paper was developed using the proposed Vibe Compiler.

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