The Presence Engine™ Living Thesis presents Human-Centric AIX™ (AI Experience), a framework for building AI systems with contextual continuity architecture instead of stateless task execution. This work addresses the fundamental gap in current AI design: systems that optimize for productivity while failing at presence, memory, and sustained human development. Grounded in Bandura’s social learning theory, Hogan’s critical thinking dispositions research, and the OCEAN personality framework, this thesis argues that AI systems train humans through repeated interaction—and current architectures are training poorly. The proposed solution: privacy-first infrastructure modeling how humans think across time rather than what they say in discrete moments. This is active research. The framework includes technical architecture, theoretical grounding, and early prototype evidence, but requires longitudinal validation. Version 3 (forthcoming) will expand technical methodology, evidence, and honest assessment of limitations. Collaboration welcome. For researchers interested in contextual continuity architecture, dispositional AI, or human-centric alignment: smith@antiparty.co