· Chapter 1: Introduction of AI Product Management: Chapter Goal : o To understand the foundation of enterprise AI. o To understand AI start-up''s landscape, including taxonomy, business value and ROI, business models, and valuation. o Case Study. · Chapter 2: Product Market Validation for B2B AI Start-ups: Chapter Goal: o To understand why we need to do AI product-market validation for B2B. o To understand when to do AI product-market validation for B2B. o To understand how to do AI product-market validation for B2B. o Case Study. · Chapter 3: Product Market Validation for B2D AI Start-ups: Chapter Goal: o To understand what is a developer-centric product.
o To understand why selling to the developer is one of the best strategies for AI products. o To understand how to do AI product-market validation for B2D. o Case Study. · Chapter 4: AI Product Strategy: Chapter Goal: o To understand the foundation of product strategy. o To understand how to do discovery for AI-related products. o To understand how to do AI product requirement analysis. o To understand how to do AI product prioritization. o Case Study.
· Chapter 5: AI Product Development in practice: Chapter Goal: o To understand the foundation of the product lifecycle. o To understand how to do User Research for AI products. o To understand how to do AI product development. o Case Study. · Chapter 6: Software Development Lifecycle for AI products : Chapter Goal: o To understand the foundation of the software development lifecycle (SDLC). o To understand how the SDLC for AI is different from traditional SDLC. o To understand DevOps and MLOps concepts, the difference, and practices. o Case Study.
· Chapter 7: Software Architecture and Team design for AI products : Chapter Goal: o To understand the importance of Conway law for AI start-ups. o To understand why data engineering and operations are the keys to successful AI start-ups. o To understand how to design scalable data-intensive software architecture. o To understand how to define a highly effective technical team o Case Study. · Chapter 8: Building effective AI Product Go-To-Market strategy : Chapter Goal: o To understand the foundation of AI start-ups'' growth strategy. o To understand the B2B and B2D sales funnels, the difference, and strategies. o Understanding AIaaS and AI-powered SaaS marketing and growth metrics. o Case Study.
· Chapter 9: Building effective AI Product Go-To-Market strategy : Chapter Goal: o To understand the foundation of AI start-ups'' growth strategy. o To understand the B2B and B2D sales funnels, the difference, and strategies. o Understanding AIaaS and AI-powered SaaS marketing and growth metrics. o Case Study. · Chapter 10: Building effective AI Product Go-To-Market strategy : Chapter Goal: o To understand the foundation of AI start-ups'' growth strategy. o To understand the B2B and B2D sales funnels, the difference, and strategies. o Understanding AIaaS and AI-powered SaaS marketing and growth metrics. o Case Study.
· Chapter 11: Recruiting and Managing AI talents: Chapter Goal: o To understand that production AI is different from academia Ph.D. o To understand how to scout and recruit AI talents. o To understand how to outsource AI development. o To understand how to manage the AI team and minimize turn-over. o Case Study. · Chapter 12: Strategizing Exit Plan: Chapter Goal: o To understand how to drive strategic value in AI start-ups. o To understand how to targeting acquisitors.
o To understand the M&A process and how to select M&A advisors. o The future of Enterprise AI landscapes. o Wrapping Up. o Case Study.