From Zero to Product with Generative AI

As I’ve mentioned before, I’ve been working on an ebook, and now it’s finally finished! It’s about 107 pages long and focuses on how today’s builders are developing apps using LLMs and other AI models. The content is a blend of technology and business—it’s not highly technical, as it centers around case studies and products, but it also dives into some implementation details. I think people in the startup world will like it. I had previewed parts of it on my blog, but now it’s fully done and available online for everyone to read.

It includes case studies on AI products and companies like Sweep, Playground, Nibble, Czat.ai, ChatGPT (of course), Fin, Strut, Meta Smart Glasses, Rewind, Humane, Rabbit, Character, and more. If you read it and would like to be featured, feel free to reach out. I’m open to expanding the content.

About the book 

In most industries, I’d be considered middle-aged or even young by some standards, having just passed 30. However, in tech—I’m old. (Can’t imagine how people who remember the dot-com bubble must feel.) This means I experienced the earlier wave of AI firsthand, which eventually became known as machine learning. I witnessed attempts to create products similar to ChatGPT using technology that we now recognize as a dead end. Archaic.

But it also means I’m uniquely equipped for this new generative age. Many topics that are new to those who recently discovered the benefits and challenges of, say, chatbots are familiar to me. I learned them the hard way. In 2015, I tried to build a company around this technology. But it was too early, and we failed. Now, I read the same pitches I once made on the landing pages of others and think, what if.

Thankfully, every failure brings gifts too, known as experience. The goal of this book is to share that experience with you, my reader, and equip you with the skills to:

• Grasp the fundamentals of generative AI based on practical case studies with just the right amount of theory
• Incorporate gen AI methods into your product design efforts
• Create new applications, ventures, and startups using generative AI technologies such as OpenAI’s GPT-4, DALL-E, or open-source alternatives like Llama and Stable Diffusion
• Hone your ability to effectively prompt these models
• Navigate the complete journey of crafting products powered by generative AI, from budget allocation and design to selecting between in-house and third-party solutions, and then to building prototypes

The book discusses various industries that could be transformed by generative AI, providing case studies to explain these impacts. It also explores both real and hypothetical examples of products to show how this emerging technology is reshaping the way the tech industry approaches the design, prototyping, and implementation of apps, services, and experiences.

Who should read it

This book is intended for intermediate-level readers eager to apply generative AI models, particularly in the realm of new product development. When I refer to “product design,” I’m talking about more than just the user experience or user interface. I mean the comprehensive, high-level process of developing a product from start to finish. Keep in mind: design isn’t just what something looks and feels like—the design is how it works.

While this book is technical in nature, coding skills aren’t a prerequisite for grasping its content. It’s tailored for professionals—be they engineers, designers, project managers, executives, or founders—who have already brought products to market and are now seeking an introductory guide to integrating generative AI into their process.

Instead of focusing too much on technical challenges, this book maintains a high-level perspective. This approach allows non-engineers to understand how they can meaningfully contribute to their team’s AI initiatives without necessarily running code themselves. For those with technical expertise, the book offers insights into practical applications of their deep knowledge of AI model internals, especially when it comes to developing and launching new applications.

If you’re not familiar with the core terminology of modern artificial intelligence—concepts such as models, prompts, training, tokens, and hallucination, to name a few—this book will provide some foundational understanding. However, we won’t dwell on these terms excessively. If you find you need a deeper dive into such topics, it would be beneficial to consult additional resources before returning to this book.

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