The paper presents six design principles for generative AI applications, addressing unique characteristics and challenges of generative AI systems. These principles aim to support two user goals: optimizing generated artifacts to meet task-specific criteria and exploring different possibilities within a domain. The principles are coupled with practical strategies for implementation through the design process or specific UX capabilities. The development of these principles involved an iterative process, including literature review, feedback from design practitioners, validation against real-world applications, and incorporation into the design process of two generative AI applications. The principles and strategies are intended to help design practitioners create effective and safe user experiences with generative AI technologies.The paper presents six design principles for generative AI applications, addressing unique characteristics and challenges of generative AI systems. These principles aim to support two user goals: optimizing generated artifacts to meet task-specific criteria and exploring different possibilities within a domain. The principles are coupled with practical strategies for implementation through the design process or specific UX capabilities. The development of these principles involved an iterative process, including literature review, feedback from design practitioners, validation against real-world applications, and incorporation into the design process of two generative AI applications. The principles and strategies are intended to help design practitioners create effective and safe user experiences with generative AI technologies.