book

Building AI-Powered Products

by Marily Nika

February 2025

Beginner to intermediate

230 pages

5h 58m

English

O'Reilly Media, Inc.

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Includes

Includes Quizzes

Why AI Product Management?Who Should Read This Book?What This Book CoversO’Reilly Online LearningHow to Contact UsAcknowledgmentsClosing Thoughts
The Stages of AI EvolutionTraditional AI (1950s–Present)Generative AI (Late 2010s–Present)Artificial General Intelligence (2030s?)Artificial Superintelligence (~2040s?)How Products Leverage AIUnique Features of AIProbabilistic NatureDependency on DataModel DriftThe Need for Model Interpretability and ExplainabilityAutomated Decision MakingScalabilityHow These Unique Features Can Impact User ExperienceSuperpowers of AI and GenAISuperpower 1: Learning from Massive Data and ContentSuperpower 2: Personalization at ScaleSuperpower 3: Automating and Optimizing WorkflowsSuperpower 4: Generating New Content and ExperiencesSuperpower 5: Prediction and ForecastingSuperpower 6: Real-Time AdaptationSuperpower 7: Unlocking New Types of User Experiences with New Form FactorsThe AI PM’s RoleThe AI PM’s Skill SetOrganizational StructuresWhy Become an AI PM?What’s Great About Being an AI PMSubtypes of AI Product Management RolesBook Road MapConclusion
Types of AI Products0-to-1 AI Products1-to-n AI ProductsThe AI Product Development LifecycleIdeationOpportunityConcept and PrototypeTesting and AnalysisRolloutConclusion
Core Product Management Craft and PracticesIdentifying User Segments, User Personas, Pain Points, and User NeedsWriting User StoriesAssessing Trade-offs and Prioritizing in AI Product ManagementBuilding or Buying? Strategic Trade-offsDefining Your Trade SpaceIncorporating Trade-offs in a Product ReviewHow to Develop General Product Management SkillsEducational PursuitsHands-on ExperienceContinuous LearningEssential Leadership and Collaboration SkillsCreativityCommunicationLeadershipAnalytical ThinkingEmpathyEngineering Foundations for Product ManagersWorking with CodeKey Technical ConceptsThe AI Product Development Lifecycle and Operational AwarenessProject ScopingData CollectionModel TrainingValidation and TestingDeploymentRemember to Keep Humans in the LoopMapping AI Algorithms and ApplicationsResponsible AI PracticesConclusion
The AI PM Career LadderExecution-Level AI Product Management (Levels 4–6)AI/ML Product Management (Levels 5–7)Strategic Leadership (Levels 8+)AI Product Manager ProfilesEthan ColeMark CramerDiego GranadosJaclyn KonzelmannArun RaoNino TascaYana WelinderMy Two CentsCross-functional CollaborationConclusion
Your Business Strategy: Evaluating AI As a SolutionAI Might Not Always Be the AnswerDisruptive or Sustaining? Navigating the Innovator’s DilemmaYour AI Strategy: To Build or to Buy?The Build-Versus-Buy Decision MatrixHybrid Approaches: A Balanced StrategyYour Data Strategy: Populating and Adapting Your ModelSynthetic Versus Real-World DataFine-tuning, RAG, or Grounding?Product Reviews: Getting Buy-in from LeadershipConclusion
Product Health MetricsSystem Health MetricsAI Proxy MetricsModel Quality MetricsObjective FunctionsConfusion MatricesOKRs for AI ProductsTying Metrics to GoalsA Framework for Crafting AI Product OKRsConclusion
Tools to Enhance the AIPDLTools for Collaboration and TrackingConclusion
What Is an AI Agent?Not Just Glorified ChatbotsEarly Rule-Based AgentsAgentive ProductsComparing Chatbots to AI Agents and Multi-agentsThe AI Agent Product LandscapeCrafting the Right AI Agent for Your ProductTask-Specific Vertical Agents Versus General-Purpose AgentsAgent ActivationAutonomyFeedback and LearningDesign Patterns for Agent InteractionSide PanelFloating BubbleChat InterfaceIntegrated UIPop-up NotificationsCollaborative Browser InterfaceScalability, Future-proofing, and Other ConsiderationsDefine Success for Your AgentAI Agent QuestionnaireConclusion
Product Review TemplateAI Product Requirements Document TemplateWorksheet 1: Assessing AI Opportunity for Your OrganizationSection 1: AI Capabilities AssessmentSection 2: Company Mission and AI AlignmentSection 3: Product Pain PointsSection 4: User ImpactSection 5: Benefits and Risks AnalysisSection 6: Resource AssessmentSection 7: Competitive AnalysisSection 8: Implementation DecisionNext StepsWorksheet 2: AI Implementation Strategy WorksheetSection 1: Core Project ComponentsSection 2: User Impact AssessmentSection 3: Benefits and Risks AnalysisSection 4: Resource AssessmentSection 5: Competitive AnalysisSection 6: Implementation Decision

Content preview from Building AI-Powered Products

Chapter 3. Essential AI PM Knowledge

In Chapter 2, we mapped the AI PM’s role to each phase of the AIPDL. Unlike their counterparts in traditional product management, AI PMs must carefully navigate advancing AI technologies in ever-changing market demands. Marrying unique product value propositions with a precise market fit gives products a competitive edge and propels industries toward groundbreaking innovations. As businesses increasingly use AI to drive decision making, optimize operations, and personalize customer interactions, the demand for skilled AI PMs has surged. These professionals are at the forefront, developing innovative products to solve unmet needs.

In this chapter, we explore the essential skills that product managers need to transition into roles focused on AI. Moving from traditional to AI product management can be done without starting from scratch. Many core skills you have honed—such as project oversight, stakeholder communication, and strategic thinking—serve as a solid foundation in this new arena. However, AI product management also demands specialized capabilities.

AI PMs must possess technical understanding and strategic foresight to navigate the unique challenges of AI products. As an AI PM, you will be more than a project overseer; you will be the visionary who can discern and balance human needs with machine possibilities. This role requires an in-depth understanding of AI technology’s potential and boundaries. While a flair for innovative solutions ...