UXDX Community:Washington, DC

AI is helping us move faster than ever, but speed is not the same thing as capacity. UX and Product leaders are expected to do more with less, lead through constant change, and deliver high-quality outcomes without burning out themselves or their teams.

This session introduces two practical leadership frameworks designed for today's reality. The first helps leaders respond when everything is urgent, providing a repeatable approach for stabilizing teams, prioritizing work, and navigating high-pressure situations. The second focuses on sustainable leadership, offering practical strategies for maintaining high performance over time through better self-management, resilience, and human-centered leadership.

Drawing from real leadership experience, burnout and recovery, and lessons learned leading Product Design organizations, this isn't another talk about productivity or AI tools. It's about the one system every leader is responsible for managing first: themselves.

Attendees will leave with practical frameworks they can immediately apply to lead with greater clarity, resilience, and confidence, without sacrificing the people behind the work.

A short welcome and introduction to the afternoon from the UXDX Washington, DC ambassadors.

Wrap up the afternoon and continue the conversation with speakers and attendees.

Without rich domain context, AI defaults to generic outputs that fall flat for both users and business goals. To build truly valuable solutions, product teams must evolve from reactive prompting to intentional context architecture that treats design systems, business logic, and user data as primary inputs. In this session, you’ll learn actionable frameworks to embed this context directly into your tooling, followed by a live prototype walkthrough demonstrating the power of an interconnected AI workflow.

Enterprise AI is moving rapidly from experimentation to production but many promising pilots still fail to become products that people can trust, adopt, and scale. What changes when we design Agentic AI not as a feature or proof of concept, but as a product that must operate across complex cloud ecosystems, business workflows, and organizational boundaries?

Drawing on her experience launching cloud and AI products at Oracle, AWS, and PwC, Rakshana Balakrishnan explores the product decisions behind moving Agentic AI from pilot to enterprise impact. By introducing the AI Mileage Framework, this session examines how product teams can design for trust, governance, security, cost, and operational reliability from the start without sacrificing experimentation and speed. This session will offer practical lessons for product managers, designers, and technology leaders building AI products that are not only impressive in a demo, but usable, trusted, and ready for the real world.