WLSP: Product Management in AI
Jennifer Wong from Smartling reviewed some AI product management traits and the difference between generic product management without AI. She talked about her current role, where she leads AI technology research and the challenges of the ever-evolving AI changes. She spoke about the double-diamond framework of product management and the request, discovery, definition, and development that comes with this framework. To add to this, she spoke about the five main pillars of product management. These pillars consist of vision and planning, stakeholder alignment, discovery of the problem and solution, definition and delivery, and the data analytics and feedback of that product development. I learned about the product vision, the roadmap features that come with the vision, and the steps geared toward tailoring it to your audience. A concept I was not too familiar with is “Stakeholder Alignment” and who is impacted by the “problem” and who will be impacted by the solution. I learned appropriate questions to ask stakeholders, such as “What value will be added by implementing this feature?” during the discovery stage. When it comes to AI in product management, Jennifer spoke about the bounds you need to set for the research team to deliver an AI product feature. As a Temple student, I’m constantly learning and adapting to new AI features and how to use them in the information technology field. Jennifer helped me understand some general product management skills and how product managers work with AI or create AI to deliver a product.