This article presents a concept for scalable autonomy of UAVs applicable to the field of reconnaissance missions. Level of autonomy can be defined along the amount of human independence. Low human independence allows detailed control, while adding to the workload. Higher human independence provides functionalities inflicting less workload, but hides information from the pilot or inhibits from interacting with the system in depth. We present a concept to facilitate a range of human independence provided by an intelligent agent onboard the UAV. This enables the interaction of the human with the automation on different echelons of control. Instead of offering access to the different automation functions directly, the operator is guided along a hierarchical task tree. This allows the system to deduce the overall purpose of human interactions and facilitates support by informing about flaws in the plan and by suggesting alternatives. The concept was implemented resulting in an agent architecture, which is based on Hierarchical Task Network (HTN) planning and reasoning with the use of the Drools rule engine. The agent is commanded using the concept of task-based guidance, which represents the highest human independence currently implemented in the system. The research for guiding multiple UAVs on a team level is planned as a next step. We conducted tests with the implemented system in a simulated environment.