A primary challenge in using ChatGPT for mobile app component reuse is its difficulty with deep contextual understanding of existing app architecture, platform-specific conventions, and unique design systems, often leading to generic components that lack true reusability. It frequently struggles to produce highly specific, production-ready components that seamlessly integrate with frameworks like React Native or Flutter, requiring significant developer effort for adaptation. Ensuring adherence to existing coding standards and design guidelines across the project becomes a major hurdle, demanding extensive human oversight and refactoring. Furthermore, validation and debugging of AI-generated components are critical, as models can introduce subtle bugs or performance bottlenecks that are challenging to identify. The AI may also face difficulties understanding complex state management or data flow typical in robust mobile applications, offering suboptimal solutions. Without extensive fine-tuning on proprietary codebases, ChatGPT tends to provide over-generalized or "hallucinated" component suggestions, necessitating substantial manual intervention to achieve true reusability and production readiness. More details: https://can.marathon.ru/sites/all/modules/pubdlcnt/pubdlcnt.php?file=https://abcname.com.ua/