Seminarie: Nine Yards

This workshop guides participants through the end-to-end process of designing, building, validating, and iterating a Minimum Viable Product (MVP) using AI. Participants will learn how to leverage modern AI tools to accelerate ideation, reduce development effort, and create data-informed follow-up cycles that turn MVPs into scalable products.

The session emphasizes practical decision-making, rapid experimentation, and continuous learning, rather than complex model building.

Learning Objectives

• By the end of the session, participants will be able to:

• • Identify where AI meaningfully adds value in an MVP (and where it doesn’t)

• • Translate a problem statement into an AI-enabled MVP scope

• • Build or prototype MVP components using AI tools and services

• • Define validation metrics and feedback loops for early users

• • Plan structured follow-up iterations based on AI-driven insights

• • Avoid common pitfalls such as over-engineering or premature scalingUser story mapping, hoe komen we tot een MVP?