Generative AI can feel like a race, but most teams are still asking the wrong first question.
We are joined by two MathWorks leaders who approach generative AI from opposite sides of the same goal: Deborah, an AI engineer working on MATLAB Copilot and AI-assisted coding, and Alicia, a commercial leader helping customers turn new capabilities into real outcomes.
We talk candidly about what it takes to move from a flashy Gen AI demo to something you can trust in production. Deborah breaks down why Gen AI is not the answer to every problem, and why problem definition, testing, and iteration matter. Alicia shares what she hears from engineers and scientists across industries, including the pressure to “use AI” and the practical reality of changing workflows, building standards, and proving impact.
Along the way, we unpack tech career misconceptions that still hold people back. Coding is only one part of building useful software; communication, user empathy, and cross-team collaboration are just as critical. We also get real about psychological safety, learning curves, and what it is like stepping into management when the market and the product roadmap can shift in six months.
If you care about Gen AI adoption, AI product development, tech careers, or how technical teams and commercial teams stay aligned, this one is for you.
