Daina Bouquin
Daina brings technical depth and community-building expertise to her role as Sr. Developer Relations Engineer at Anaconda. With over 12 years bridging data science, library science, and open source advocacy, she's spent her career making complex technology more accessible to researchers and practitioners. Her work has included pioneering software citation and preservation initiatives at the Harvard-Smithsonian Center for Astrophysics and developing AI evaluation frameworks for federal agencies. This experience has given her insight into both the technical challenges developers face and the human side of adopting new tools. At Anaconda, she works to strengthen connections between Anaconda's engineering teams and the broader developer community, creating resources and fostering relationships that help people solve important problems with open source tools.
Session
Your LLM evaluation suite shows 93% accuracy. Then domain experts point out it's producing catastrophically wrong answers for real-world use cases. This talk explores the collaboration gap between AI engineers and domain experts that technical evaluation alone cannot bridge. Drawing from government, healthcare, and civic tech case studies, we'll examine why tools like PromptFoo, DeepEval, and RAGAS are necessary but insufficient and how structured collaboration with domain stakeholders reveals critical failures invisible to standard metrics. You'll leave with practical starting points for building cross-functional evaluation that catches problems before deployment.