In the race to build smarter systems, we obsess over precision and performance, yet lose sight of the quietest threat of all: indifference. It’s the unnoticed drag inside every AI and data project: the meetings, models, and motions that look productive but deliver no real progress.

In this talk, Jade introduces The Indifference Trap, a framework for identifying and eliminating silent inefficiencies in data and AI workflows.

Drawing from her diversified experience, from engineering data for AI agents, designing and embedding innovative data solutions, driving strategic decisions and guiding teams from idea to value impact; Jade shares how to reclaim focus, velocity, and purpose — turning complexity into clarity, and code into outcomes that matter.