What this book covers

Chapter 1, Introducing Microsoft Semantic Kernel, introduces several AI concepts and gives a tour of what Semantic Kernel can help you achieve, showing you how to connect to an AI service and use it to achieve a goal.

Chapter 2, Creating Better Prompts, teaches you several techniques on how to interact better with AI, improving the chances that you will get a good result on your first try, using a concept called prompt engineering.

Chapter 3, Extending Semantic Kernel, teaches you how to add functionality to Semantic Kernel, by adding native functions and semantic functions that can later be reused by you, as a developer, or your user to achieve their goals.

Chapter 4, Performing Complex Actions by Chaining Functions, shows you how to use several functions of a kernel in sequence, making programming complex actions a lot easier.

Chapter 5, Programming with Planners, explores how Semantic Kernel can receive a request in natural language and automatically decide which functions to call to achieve an objective, allowing users of your application to perform functions that you did not have to write code for.

Chapter 6, Adding Memories to Your AI Application, examines how to add external knowledge to the AI models used by Semantic Kernel, making it easier for AI models to remember recent conversations and personalizations.

Chapter 7, Real-World Use Case – Retrieval-Augmented Generation, shows how to add a large amount of data to AI models, allowing them to efficiently use information that they have not been trained on, including very recent and private data.

Chapter 8, Real-World Use Case – Making Your Application Available on ChatGPT, shows how to publish the application you wrote with Microsoft Semantic Kernel on OpenAI’s GPT store, making it instantly available to millions of users.