Is Your AI Project Flying Blind?

Imagine this: Your team has spent nine months developing a sophisticated AI-powered recommendation engine. The data science is brilliant, the model's accuracy is impressive in the lab, but early user feedback is lukewarm. Users don't trust the "black box" recommendations, the engineering team is struggling to adapt to constantly changing data requirements, and leadership is questioning the ROI. You have powerful technology, but no clear path to a product people will actually use and love.

This scenario is all too common. In the age of AI, technical feasibility is no longer the biggest hurdle—achieving genuine product-market fit is. This lecture is a deep dive specifically for the builders and visionaries on the front lines of AI innovation who need a proven framework to navigate this complexity.

We will deconstruct the false choice between Design Thinking vs. Lean Startup vs. Agile and reveal how to strategically integrate them into a unified playbook for developing successful AI products. We're moving beyond the textbook definitions to address the unique challenges of AI development, from handling probabilistic outcomes to designing for user trust and managing iterative model training within development sprints.

In This LIVE Session, You Will Learn To:

Apply Design Thinking to Frame the Right AI Problem: Learn techniques to move beyond "what can the model do?" to "what human problem should our AI solve?" We'll cover specific methods for empathizing with users and mitigating ethical risks and algorithmic bias from day one.

Use the Lean Startup to De-Risk Your AI Venture: Discover how to design and run low-cost experiments to validate your core AI hypotheses. Learn what a true "AI MVP" looks like and how to gather meaningful market data before committing to full-scale engineering.

Adapt Agile for the Nuances of AI/ML Development: Explore practical strategies for integrating the non-deterministic work of model training and data science into predictable, two-week sprints. We'll discuss how to structure backlogs, define "Done" for a machine learning task, and plan for continuous model improvement.

Fuse the Three Methodologies into a Cohesive Strategy: Walk away with a practical roadmap illustrating when to leverage each framework throughout the AI product lifecycle—from initial ideation and ethical review to building, testing, and scaling your solution.

Who Must Attend:

This is not a high-level theoretical overview. It is a tactical session designed for:

Product Managers & Product Owners responsible for defining the vision, strategy, and roadmap for AI features.

AI/ML Engineers & Data Scientists who want to better understand the product context of their work and collaborate more effectively with their teams.

UX/UI Designers & Researchers challenged with creating intuitive, trustworthy, and human-centered interfaces for AI systems.

Startup Founders & Tech Leads who are building AI-first companies and need a capital-efficient framework for finding product-market fit.

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Welcome to MOMENTUM+ Innovation School!

[mantra: learn the essential playbook for turning powerful technology into products that win in the market]

Startups+/understand design thinking vs. lean startup vs. agile