One of the most crucial hinges in any software eco-system is how product management collaborates with engineering. This workshop will cover how product managers can create the right conversations, establish trust and extract information out of their engineering teams. Engineering teams are increasingly working with AI/ML capabilities, LLMs, and complex data pipelines. Product managers must understand how to develop AI use cases, scope AI features, communicate technical constraints, and help organizations make smart trade-off decisions. In a world where development is moving faster than ever,
This program will cover:
Developing AI use cases in partnership with engineering
Project inceptions for AI feature development - aligning on goals, risks, data requirements
User story writing for AI/ML features with clear success criteria
User story mapping with technical dependency visualization for AI capabilities
Backlog management for iterative AI model development
Retrospectives that address AI-specific learnings (model performance, data quality, user acceptance)
Outcomes:
PMs will create efficient documentation that clearly scopes AI feature requirements and constraints
PMs will understand how to collaboratively plan AI feature implementation with data and ML considerations
PMs will effectively communicate AI capability trade-offs to stakeholders
Product Managers will collect feedback on AI feature performance and iterate based on user behavior data
PMs will build trust with engineering through clear communication of AI product requirements and realistic expectations