The most effective product ops teams aren't improving AI adoption and cross-functional collaboration in isolation; they're combining both to fundamentally transform how they plan, prioritize, and deliver. When AI-powered workflows meet genuinely aligned teams, the results can be transformative. This panel explores what happens at the intersection of these forces, how leading organizations are deliberately connecting them, and what it means for the future of product operations. Panellists will share concrete examples of where AI and collaboration have combined to unlock outcomes that neither could have achieved alone.

AI products cannot be managed with “gut feel” alone. As AI systems become increasingly agentic, multimodal, and autonomous, product teams need new ways to define quality, measure reliability, and operationalize trust at scale. In this highly interactive Product Lab workshop, Balachander Keelapudi and Madhuri Peri from AWS lead a hands-on session exploring how teams can use specs, evals, and structured testing frameworks to build more reliable AI products and agentic workflows. Designed for product, operations, and transformation leaders - including those without deep engineering backgrounds - the workshop focuses on practical implementation rather than theory. Through live exercises, collaborative problem-solving, workflow examples, and real-world case studies, attendees will explore: - how to design meaningful AI evaluations, - the difference between traditional QA and AI eval frameworks, - how to define success criteria for AI agents, - identifying failure modes and operational risks, - and how product teams can improve AI reliability without slowing innovation. Participants will leave with practical frameworks, implementation approaches, and actionable methods they can apply immediately within their own AI products and workflows.