Imagine a digital world where every click, every swipe, every interaction is tailored precisely to you. No more one-size-fits-all designs, but interfaces that adapt to your individual needs and preferences in real-time. This is the promise of adaptive UX, and a new research paper explores how AI can make this a reality. Traditionally, user experience (UX) design has been a static process, creating interfaces for the "average" user. But users aren't average. We have diverse needs, preferences, and goals when interacting with software. This research introduces a novel approach using Large Language Models (LLMs), the technology behind AI assistants like ChatGPT, to create dynamic and personalized user experiences. The key is combining the power of LLMs with detailed user personas. Personas are archetypical user profiles that represent the characteristics, goals, and behaviors of specific user groups. By feeding these personas into LLMs, designers can generate interfaces that cater to a wide range of individual needs. This research delves into three key areas: understanding current adaptive UX practices, exploring the role of personas in UX adaptability, and proposing a framework that leverages LLMs to generate dynamic UX designs and guidelines. The potential implications are vast. Imagine websites that automatically adjust their layout and content based on your past browsing history, or mobile apps that personalize their features based on your current location and activity. However, challenges remain. Effectively using LLMs for UX design requires careful prompt engineering, ensuring the AI understands the nuances of user needs and preferences. Furthermore, rigorous evaluation and feedback from real users are crucial to refine the generated interfaces and ensure they truly meet diverse needs. This research lays the groundwork for a future where technology adapts to us, not the other way around, creating a more inclusive and user-centered digital world.