The AI Revolution is Just Beginning

Since ChatGPT's landmark debut in late 2022, we've witnessed a seismic shift in how businesses and consumers view AI. What started as a fascinating chatbot has sparked a fundamental transformation across industries. Large Language Models, once considered cutting-edge, are now table stakes. As we move from GenAI to Agentic AI, the pace of innovation shows no signs of slowing.

The message is clear: AI isn't just another tech trend—it's becoming the core of how products and services will be built and delivered. Whether you're in B2C or B2B, your products will either evolve to leverage AI or risk becoming obsolete.

The AI Execution Challenge

But here's the paradox: While AI technology races forward, many product teams are still struggling with the basics of building successful AI products. If you're a product or design leader, you've likely experienced the pressure to "get something out there with AI." Companies are rushing to implement solutions, driven by top-down mandates, competitive pressure, or technological FOMO.

The reality? Successful AI products aren't born from rushing to implementation. They come from thoughtful strategy, careful validation, and deliberate planning that creates genuine value for users and business.

Right now, teams are:

- Jumping into AI implementation without proper strategic deliberation

- Struggling to identify which problems truly need AI solutions

- Missing alignment with critical user needs in the rush to deploy

- Lacking frameworks to evaluate and validate AI opportunities

- Unable to effectively communicate the "why" behind AI initiatives

But does it have to be this way?

You can learn to evaluate and strategize AI initiatives with confidence. You can develop clear frameworks for validating AI opportunities. You can create compelling roadmaps that align stakeholders around a shared vision.

This is exactly what you'll master in this course.

What you will learn:

- How to identify which problems truly need AI solutions

- How to evaluate AI opportunities using proven frameworks

- How to build user trust in AI through thoughtful design

- How to craft AI experiences users will actually adopt

- How to validate AI features before heavy investment

- How to choose the right AI interfaces for your use case

- How to define data requirements for AI success

- How to plan for responsible AI implementation

- How to measure AI product success meaningfully

- How to communicate AI strategy to stakeholders

- How to align teams around your AI vision

- How to create AI roadmaps that drive real value

- How to assess technical feasibility early

- How to prototype AI features with no-code tools to get buy-in

Our Approach

This course is designed to transform how you think about and approach AI product opportunities.

If you engage fully with the course, you'll make a fundamental shift from "How do we add AI to our product?" to "How do we strategically create value with AI?" You'll develop the muscle memory to instantly recognize good AI opportunities, ask the right questions, and make informed strategic decisions.

Throughout the program, we'll move beyond theoretical frameworks to tackle real challenges you're facing through AMA sections of the workshop.

We'll explore the nuances of different AI use cases, examine edge cases that challenge conventional thinking, and work through examples that build your strategic instincts. Every framework and approach we teach comes from real-world experience leading AI initiatives—successes and failures included.

We've specifically designed this course to build your confidence through practice. Each week builds upon the previous learnings, helping you develop a natural intuition for AI product strategy.

All sessions are recorded, and frameworks are documented so you can revisit and reinforce your learning as you lead future AI initiatives.