As the integration of LLMs and Typescript advances, it is crucial to address the ethical implications and best practices for developing agentic workflows. In this chapter, students will explore the ethical challenges, such as bias, transparency, and accountability, that arise when deploying these intelligent systems. They will also learn about responsible AI principles, data privacy and security measures, and techniques for maintaining user trust and acceptance. By the end of this chapter, students will be equipped to navigate the ethical landscape and implement agentic workflows that prioritize user well-being and societal benefit.