In this paper we present the results of our investigation into how employees at Microsoft, as early adopters of multi-agent generative AI systems, navigate the complexities of designing, testing, and deploying these technologies to extend the organization's product ecosystem.Through interviews with thirteen developers, we uncover the challenges, use cases, and lessons when designing with and for multi-agent AI frameworks.Our analysis reveals how participants leveraged this advanced emerging technology to enhance collaboration, productivity, customer support, creative processes, and security.Key design strategies include managing agent complexity, fostering transparency, and balancing agent autonomy with human oversight, essential considerations for human-agent interaction design.We provide empirical insights into the capabilities and limitations of multi-agent systems in real-world contexts, informing the design of future AI systems that align AI capabilities with human-centered design.By emphasizing first-person experiences and strategies, our research bridges human needs and AI potentials, advancing both the practice and theory of designing with and for AI systems.

As generative AI tools become integrated into design workflows, students increasingly engage with these tools not just as aids, but as collaborators.This study analyzes reflections from 33 student teams in an HCI design course to examine the kinds of judgments students make when using AI tools.We found both established forms of design judgment (e.g., instrumental, appreciative, quality) and emergent types: agency-distribution judgment and reliability judgment.These new forms capture how students negotiate creative responsibility with AI and assess the trustworthiness of its outputs.Our findings suggest that generative AI introduces new layers of complexity into design reasoning, prompting students to reflect not only on what AI produces, but also on how and when to rely on it.By foregrounding these judgments, we offer a conceptual lens for understanding how students engage in co-creative sensemaking with AI in design contexts.

Through this poster submission I present my ongoing investigation into the dynamics of interpersonal relationships within online fandom communities, specifically focusing on the BTS fandom community known as ARMY. Amid the digital era’s paradox of increased content creation and consumption alongside declining meaningful social interactions, I hope to identify online fandom communities as unique spaces where interpersonal relationships not only thrive but contribute to the sustainability of these digital communities. Using a case study approach on the ARMY fandom, which expanded during the pandemic, my research aims to dissect the nuances of relationship formation and sustainability. Through a combination of literature review, online diary studies, interviews, and digital ethnography, I explore how fans engage, and support each other, nurturing a sense of community. Initial findings highlight the interplay between personal and collective identity formation, the supportive role of community spaces, the impact of social support on well-being, and a profound sense of belonging among members. This study offers valuable perspectives on designing digital spaces that foster strong social connections.