This study presents a structured methodology for AI-driven systems that foster metacognitive development in higher education. Built on the cognitive apprenticeship-based (CAB) framework, it includes an instructional framework, system model, and multi-agent architecture. Each layer translates pedagogical principles such as modeling, scaffolding, and reflection into intelligent agent behaviors. The resulting ecosystem supports personalized, ethical, and pedagogically coherent learning. Design principles include thinking-centeredness, human–AI partnership, and data-driven orchestration. A phased deployment roadmap supports scalable integration. This work provides a foundation for AI enhanced learning that promotes metacognitive thinking.