AI MVP Sprint
From Idea to AI-Powered Prototype
A guided 6–8 session program designed to help individuals turn ideas, workflows, or business problems into practical AI-powered MVPs (Minimum Viable Products).
Program Goals
Ideal For
- ✓ Professionals exploring AI product ideas
- ✓ Individuals with workflows they want to improve using AI
- ✓ Early-stage builders and side-project creators
- ✓ Non-technical or semi-technical learners who want practical guidance
- ✓ People who feel stuck turning ideas into execution
Advisors and Coaches
Participants are guided by a group of coaches with deep industry and domain experience. The exact lineup may vary by cohort and project focus.
Su Huang
Business, Data Science, and Real-World AI Applications
Su Huang specializes in helping participants connect AI ideas with real-world business problems and practical execution. His background spans business analytics, data science, retail operations, and AI-driven decision making across large-scale technology environments.
With experience in areas such as retail strategy, customer behavior, pricing, operations, and analytics, he focuses on helping participants better define problems, evaluate business value, structure practical AI workflows, and communicate project impact effectively. His coaching emphasizes turning ideas into realistic and meaningful AI-powered solutions.
Read full profile →Denny Wang
AI Engineering, Workflows, and Prototype Development
Denny Wang specializes in helping participants turn ideas into working AI-powered prototypes. His background includes software engineering, AI technologies, system workflows, and practical implementation across modern technology environments.
He focuses on helping participants design technical architectures, evaluate implementation approaches, build functional MVPs, and navigate real-world engineering challenges during the prototyping process.
Read full profile →Yingchao Zhang, Ph.D.
AI Strategy, Operations, and Real-World Applications
Dr. Yingchao Zhang specializes in helping participants connect AI ideas with practical organizational and operational needs. His background spans AI startups, enterprise systems, operational strategy, and technology leadership.
He focuses on helping participants evaluate AI opportunities, refine practical use cases, and think strategically about how AI solutions can create meaningful real-world impact.
Read full profile →Lynn Shawn
Cross-Functional Strategy, Product Thinking, and AI Execution
Lynn Shawn specializes in helping participants structure complex ideas into practical and executable AI projects. Her background includes AI strategy, product analytics, machine learning organizations, and cross-functional leadership across large technology companies.
She focuses on helping participants scope realistic solutions, align technical and business perspectives, improve project communication, and navigate complex problem-solving environments throughout the MVP building process.
Read full profile →Sample Session Breakdown
Below is one example of how the program could be structured. Each cohort is shaped around its participants' goals, backgrounds, and projects, so the actual flow and pacing may look different.
Problem Identification & MVP Thinking
"What problem are we actually solving?"
Learn how to identify meaningful AI opportunities instead of chasing random AI ideas.
- Initial project idea
- Problem statement draft
Understanding the AI Landscape
"What tools and approaches actually make sense?"
Understand how to evaluate AI tools and choose practical solutions instead of getting overwhelmed by the fast-changing AI ecosystem.
- Initial solution direction
- Tool selection plan
Architecture Design
"How do we design a scalable and secure system?"
Learn how to design system architectures that are scalable, secure, and production-ready — even at the MVP stage.
- Architecture diagram
- Component design document
- Security and scalability checklist
Building the Prototype (Part 1)
"Turning ideas into something usable"
Experience how rapid AI prototyping works in practice.
- Early prototype draft
Building the Prototype (Part 2)
"Testing and improving the MVP"
Learn how to iterate, debug, and improve imperfect AI systems.
- Functional MVP prototype
AI Product Thinking & Real-World Usage
"Would people actually use this?"
Understand that successful AI products solve meaningful user problems, not just technical challenges.
- Refined MVP direction
- Usage scenario plan
Storytelling & Presentation
"How do you explain the value clearly?"
Learn how to communicate AI ideas and real-world impact clearly.
"If you cannot explain something in simple terms, then you don't understand it." — Richard Feynman
- Demo-ready presentation
Final Demo Day & Next Steps
"From prototype to future opportunities"
Gain confidence turning ideas into real AI-powered solutions.
- Final MVP showcase
- Personal next-step roadmap
Book a Free Consultation
Not sure where to start? Book a free 30-minute call and we'll help you figure out the right path.
No commitment. No sales pitch. Just a conversation about your goals.