Online courses are now a permanent feature of the post–COVID-19 higher education landscape, while generative artificial intelligence (GenAI) has rapidly become a common tool for college students. Although GenAI offers new possibilities for learning, it also raises growing concerns about originality and academic integrity, particularly in online classrooms. This interactive talk explores practical strategies for designing GenAI-resistant course assessments in online undergraduate agriculture programs. Rather than focusing on detection or prohibition, the session emphasizes assessment design that encourages creativity, critical thinking, and authentic student engagement. Grounded in existing coursework from a sustainable agriculture undergraduate program, the workshop draws on instructor observations, peer-reviewed evaluation surveys, and student reflections. Attendees will explore examples of context-rich and process-oriented assignments that require students to apply course concepts. Findings suggest that thoughtfully designed assessments can significantly reduce reliance on GenAI while simultaneously strengthening learning outcomes and student ownership of their work. This talk invites educators to move beyond fear-based responses to GenAI and toward innovative, learner-centered assessment practices that acknowledge AI’s growing role in everyday life while reaffirming the value of human insight and experience.