Recent advances in large language models (LLMs) have enabled the replication of speech patterns and philosophies of prominent historical figures. However, generating dialogue that reflects the philosophies of prominent leaders in small communities, such as founders of local universities or small businesses, remains a challenge due to the limited availability of public data. Nevertheless, the philosophies of such leaders often serve as important educational and behavioral foundations for members of these communities. In this study, we propose a dialogue generation method that enables the sharing of a prominent local leader’s philosophy through natural conversation. Specifically, we classify sentences left behind by the leader—such as those in books or diaries—into four types: statements, thoughts, actions, and facts. We then perform two-stage fine-tuning using the statements and thoughts to generate dialogues that faithfully reflect the leader’s values and philosophy.