This chapter presents a unique application of Large Language Models (LLMs) to enhance human-machine collaboration, specifically focusing on the operation of Unmanned Aerial Vehicles (UAVs) in urban environments. The development of a universal framework embedding LLMs to act as UAV “Co-Pilots” is explored, enabling the UAVs to interpret and execute human intentions accurately while optimizing interaction through a well-defined utilization workflow. A context management mechanism is introduced to systematically manage the information involved in these tasks. Additionally, the chapter outlines a collaborative control framework for large-scale UAV deployments, addressing computational and communication challenges by predicting environmental changes and optimizing information exchange. The potential of hybrid intelligence-combining human insights with machine autonomy-is emphasized, showcasing the practicality and future potential of LLMs in facilitating autonomous UAV operations in complex urban scenarios. Key discussions cover the integration of LLMs into existing UAV systems, potential challenges, and prospective advancements, establishing the groundwork for improved human-machine interactions in real-world applications.