The field of autonomous aerial intelligence is rapidly evolving, driven by recent advances in Agentic AI. Researchers are now focusing on developing systems that can operate adaptively in complex, real-world environments, exhibiting goal-driven behavior, contextual reasoning, and interactive autonomy. A key area of research is the development of frameworks and architectures that can enable safe, compliant, and economically viable UAV operations in low-altitude airspace. Another important direction is the integration of multi-domain sensing, high-precision positioning, and intelligent communication to facilitate dynamic airspace management and UAV operational services. Noteworthy papers in this area include: UAVs Meet Agentic AI, which provides a comprehensive foundation for understanding the architectural components and enabling technologies of Agentic UAVs. Aerial Shepherds, which introduces a new framework for hierarchical localization in heterogeneous MAV swarms, achieving a collaborative, adaptive, and cost-effective localization system. Safe and Economical UAV Trajectory Planning, which proposes a novel hybrid DRL-LLM approach for UAV trajectory planning, enabling safe, compliant, and economically viable path planning. Toward Low-Altitude Airspace Management, which proposes a unified cellular-native architecture for LAE, integrating multi-domain sensing, high-precision positioning, and intelligent communication. Grounded Vision-Language Navigation, which proposes a framework for vision-and-language navigation tailored for UAVs, enabling open-vocabulary goal understanding and generalized navigation capabilities.