Summary

This concludes Part 1. We started with an introduction to AI and the infrastructure required to support it, went into the weeds of model maintenance and the particulars of ML and deep learning, saw a mix of applications and business model examples of AI products, and concluded with a glimpse into where AI is going next. Part 2 will expand on the AI native products themselves by focusing on what it takes to understand, ideate, create, and productize AI. We will also explore how AI products can be customized and how performance can be optimized, as well as going into some examples of common pitfalls and successes a product manager can run into with the AI native product.

In the next chapter, we will be looking at what areas are essential when you’re building an AI-native product. We will be looking at the particulars of managing a product from the ground up, with certain AI considerations and what product managers will need to account for as they begin the process of ideating...