Topics Covered

• Introduction to Agile, Scrum, and AI – basics of Agile methodologies, Scrum framework, and AI technologies that support Agile practices.

• Product Owner and Product Manager roles & responsibilities – common patterns in PO vs. PM roles and how AI can augment these roles.

• Design Thinking – what is Design Thinking and the double diamond process.

• Crafting a product vision with AI insights – AI-driven market and consumer sentiment analyses to create a more effective product vision and strategy.

• Personas and empathy mapping – leveraging AI to analyze customer interviews, create detailed personas, perform empathy mapping, and gather feedback through AI simulations.

• Adopting an incremental interactive approach – the preferred method for building products incrementally and iteratively to maximize value and flexibility.
• Continuous discovery and transparency of the product discovery life cycle – common steps in the product discovery life cycle, epic/feature Kanbans for visibility.
• Product Backlog – the basic principles of effective backlog management.
• Writing epics and features – leveraging AI to craft impactful Epics and Features that align with user needs and business goals.
• User Story Mapping – Breaking down large features into MVPs/MMFs using User Story Mapping and AI tools to refine and prioritize effectively.
• Writing user stories  – enhancing user story writing and acceptance criteria via AI.
• Story splitting – common splitting patterns, leveraging AI to split real stories.
• Prioritizing – prioritizing large items (features/epics) via WSJF and prioritizing user stories.
• Roadmapping – considerations and best practices for effective roadmapping and release planning.
• Enhancing UX with AI – leveraging AI to predict user behavior and automate A/B testing to refine user experiences.
• Visibility and KPIs for a data-driven approach – closing the feedback loop of value, commonly used KPIsE