An immersive, hands-on bootcamp for product leaders and innovators ready to thrive in the AI era. By day's end every participant leaves with a validated AI product concept, a clear user journey and a pitch-ready plan — equipped to lead AI-powered products from idea to launch.
An immersive, hands-on bootcamp designed for product leaders and innovators ready to thrive in the AI era. Participants master the fundamentals of AI product management, learn to frame real-world problems, design user-centric AI experiences, and define MVPs that balance ambition with feasibility.
Through practical sessions, teams map user journeys, identify AI opportunities and prototype solutions — covering everything from risk assessment to metrics and go-to-market strategy.
A team-based path from raw AI prompt to a structured, pitch-ready product concept — applied product thinking the whole way.
Welcome and orientation, project prompt reveal and balanced team formation, then rapid team alignment on roles, working styles and first problem framing — core user, job-to-be-done and the biggest unknowns.
Deliverable · Balanced team + framed problemCut through the hype and focus on what works. The core principles of AI product management — pattern matching, reasoning, summarization, classification and generation — building intuition for feasibility and spotting fantasy concepts.
Apply structured product thinking to define the primary user, articulate pain points and pinpoint where AI delivers real value. Surface technical, data, behavioral and ethical risks, assumptions and unknowns.
Deliverable · Reasoned problem definitionExplore the UX realities of AI products. Design flows that gracefully handle uncertainty, errors and unpredictability, master human-in-the-loop mechanisms and fallback states, and scope a realistic, valuable MVP.
Transform problem framing into a concrete user experience. Map the journey, define AI touchpoints, plan for ambiguity and failure modes, and design both the happy path and critical edge cases.
Deliverable · User journey + AI flow mapMeasure success in AI products by aligning user outcomes, business impact and technical stability. Understand product vs model metrics, and strategies for managing data requirements and operational risk.
Bring everything together into a compelling, structured concept — problem statement, user journey, AI interaction model, data needs, measurement approach and MVP definition. Ambitious yet realistic.
Deliverable · Pitch-ready product conceptPitch your AI product concept in a concise, high-impact format — problem, user, solution, AI flow, feasibility, risks, metrics and MVP — with targeted feedback from judges and facilitators (7 min pitch + 3 min feedback per team).
Reflect on the day, capture key takeaways and turn them into a shortlist of initiatives and experiments to bring back to your team, closing with open networking.
Deliverable · Action shortlist + communityThe Product AI Bootcamp brings together product managers, founders, designers and tech-savvy leaders who want to turn AI from a vague idea into clear product decisions, user journeys and launch-ready concepts.
Over one intensive day, you'll move from problem framing to UX flows, metrics and final pitches — practicing real AI product work in teams. If you want to lead AI initiatives with confidence, design trustworthy AI experiences and align cross-functional teams around a realistic, pitch-ready concept, this bootcamp is for you.
Welcome and orientation, project prompt reveal, team formation and rapid alignment on roles and first problem framing.
Core principles of AI product management and building intuition for feasibility versus fantasy concepts.
Define the user and pain points, pinpoint where AI adds value, and surface risks, assumptions and unknowns.
UX realities of AI products — uncertainty, errors, human-in-the-loop, fallback states and MVP scoping.
Map the user journey and AI touchpoints, plan failure modes, and design happy path plus edge cases.
Define success metrics, distinguish product from model metrics, and manage data and operational risk.
Finalize problem, journey, AI interaction model, data needs, measurement approach and MVP definition.
Pitch the full concept and receive targeted feedback from judges and facilitators (7 min pitch + 3 min feedback).
Reflection, key takeaways and an action shortlist, closing with open networking.
Missed the bootcamp? Catch the sessions on demand, then keep building your AI product craft — bring AI product thinking to your team with a corporate program, or grow on your own with an individual training path.