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| Part I: Identifying and Developing the Opportunity |
Lecture 1: Introduction to AI-First Products |
Why build an AI-first product company?
The evolution of AI and its transformative potential
Challenges in building an AI company today
Differentiating your AI company in a crowded market |
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Lecture 2: Market Validation and Opportunity Assessment |
Identifying customer needs and market gaps
Analyzing competitive landscapes in AI sectors
Sizing market opportunity using frameworks (TAM, SAM, SOM) |
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Lecture 3: Identifying and Validating Product Ideas |
Conducting user research to validate product ideas
Identifying and achieving product-market fit
Differentiating between a Minimum Viable Test (MVT), Minimum Viable Product (MVP), and Minimum
Lovable Product (MLP) |
| Part II: Building the Product and Company |
Lecture 4: Developing the Product |
The critical role of timing and assembling the right team
Choosing your entry point: finding the beachhead market
Embracing pivot, iterate, and kill loops in product development
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Lecture 5: Differentiation and Defensibility |
Strategies to differentiate your product in a competitive market
Building business defensibility via network effects and proprietary technology
Specific challenges and opportunities in applying these concepts to AI |
| Part III: Growing the Business |
Lecture 6: Traction, Growth, and Monetization |
Establishing key metrics and measurement frameworks for growth
Building a sustainable business model tailored for AI products
Customer acquisition, retention strategies, and lifecycle management |
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Lecture 7: Go-To-Market Strategy |
Crafting a compelling go-to-market (GTM) strategy
Identifying and leveraging optimal marketing channels
Positioning and messaging for an AI-first product |
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Lecture 8: Selling and Growing Market Share |
Sales strategies for both B2B and B2C AI products
Exploring inorganic growth avenues (partnerships, mergers, acquisitions)
Tactics for capturing and expanding market share |
| Part IV: Financing |
Lecture 9: Fundraising I – Founder Considerations |
Overview of funding stages (Seed, Series A, etc.) and their implications
Understanding dilution and its impact on founder equity
Crafting a compelling pitch deck |
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Lecture 10: Fundraising II – Investor Considerations |
The VC funding decision-making process
Key elements of term sheets and negotiation tactics
Best practices and “rules of thumb” in fundraising |
| Part V: Scaling Considerations |
Lecture 11: Scaling & Exits |
Strategies for hiring, compensation, and team scaling
Tactics for international growth and expanding product lines
Exit strategies including IPOs, mergers, and acquisitions |
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Lecture 12: Responsible AI, Legal and Regulatory Considerations |
Building trust and ensuring user acceptance of AI solutions
Intellectual property protection, copyright laws, and open source implications
Navigating the regulatory landscape for AI products |
| Part VI: Pitch Day |
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Recap of course learnings and key takeaways
Best practices and common pitfalls in building an AI startup
Future trends and the evolving landscape of AI entrepreneurship
Student presentations of capstone projects |
