AI as Wellbeing Coach: A Practical Application Architecture for the 2D State of Being Model

This paper describes the design of a wellbeing application grounded in the 2D State of Being model and a four-pillar framework. The model provides a structured way to understand human experience, but when translated into daily practice it presents users with 25 subcategories across four life domains. Without intelligent guidance, this level of granularity can overwhelm users and reduce the likelihood of sustained engagement. The proposed application addresses this challenge by helping users assess their current state and make manageable, high-impact changes. Artificial intelligence plays a central role as a coach that prioritizes and sequences recommendations rather than presenting users with an unmanageable number of options. A key insight distinguishes this application from conversation-based AI ethics tools: unlike conversational vectors, task vectors are directionally reliable and can be matched to specific pillar categories with genuine predictive validity. With appropriate privacy protections and informed user consent, aggregated data from app usage could later support the validation and refinement of the underlying model. The paper outlines the user-centered rationale for the application, the task vector framework that enables AI coaching, the supportive role of AI, the ethical considerations surrounding future data use, and an invitation to collaborate on development.