Master the art of building generative AI products with strategic frameworks, practical methodologies, and real-world insights for product managers and leaders.
The generative AI revolution is creating unprecedented opportunities for product innovation, but success requires more than just integrating the latest AI models. This comprehensive playbook provides product managers, entrepreneurs, and business leaders with the strategic frameworks and practical methodologies needed to build, launch, and scale successful generative AI products.
From understanding customer needs and defining product vision to navigating technical challenges and achieving market fit, this book covers the complete product lifecycle. We explore how to leverage AI capabilities effectively, design intuitive user experiences, and build sustainable competitive advantages in the rapidly evolving AI landscape.
Whether you're building your first AI-powered product or looking to enhance existing offerings with generative AI, this playbook provides actionable insights, proven methodologies, and real-world case studies to help you navigate the complexities of AI product development and achieve lasting market success.
Have questions about AI product development? Want to explore specific frameworks or methodologies? Chat with an AI assistant that specializes in product management and the content of this book.
Access tools, frameworks, and best practices from AWS to accelerate your AI product development journey.
Create AI applications quickly for voice of customer analysis, writing Amazon-style PRFAQs, summarizing product feature requests, and other product management use cases without coding.
Start BuildingAI-powered platform for vibe coding and building full-stack web applications to showcase internally. Create apps by simply describing what you want in plain English.
Try LovableOpen source alternative to Lovable that you can deploy in your own stack. Build web applications with AI assistance while maintaining full control.
View on GitHubAWS sample implementation for classifying and analyzing customer feedback using Amazon foundation models to extract insights for product development.
View on GitHubNatural language processing service to extract insights and relationships from customer feedback, reviews, and product requests.
Explore ComprehendConvert customer interviews, support calls, and voice feedback into text for analysis and product insights.
Learn TranscribeBuild and scale generative AI applications with foundation models from leading AI companies through a single API.
Explore BedrockFully managed machine learning service for building, training, and deploying ML models at scale for product features.
Explore SageMakerIntelligent search service powered by machine learning to help users find information quickly and accurately in your products.
Discover KendraReference implementation for a generative AI chatbot that can be customized for product use cases and customer support.
View on GitHubA solution that helps you build, deploy, and share generative AI applications quickly and securely for product teams.
View on GitHubOpenAI-Compatible RESTful APIs for Amazon Bedrock to simplify integration with existing product applications.
View on GitHubStep-by-step guide for implementing your first generative AI solution on AWS for product teams.
View on GitHubFastest way to build, deploy, and host scalable web and mobile apps with built-in AI capabilities for product prototypes.
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Meet the authors behind this book.
