Development of the generative artificial intelligence has made notable progress over recent years. Especially with the exponential prevalence of the large language models and foundation models. Although there is extensive research on the improvements of the algorithms, users often need to provide complex prompts if they want to filter the credible responses in specific domains. To improve the interaction and learning experience between users and the generative artificial intelligence system, this paper presents the literature that aims to identify research gaps and introduce the development of a Domain-Tailored Generative AI system. This domain-tailored generative AI system is designed to provide in-depth domain-tailored response for the users and to improve the effectiveness and positive impact for the users.