aie-book

This repository accompanies the book "AI Engineering" by Chip Huyen, published in 2025. The book covers how to build real-world applications using foundation models — a category that includes large language models (LLMs, the kind that power chatbots) and large multimodal models (models that can handle both text and images). The repository provides supplementary materials: chapter summaries, study notes, prompt engineering examples, case studies, an appendix, and a list of AI engineering resources.

The book itself is not a coding tutorial with lots of code snippets. Instead, it is a conceptual and practical guide for engineers and technical roles who want to understand the full process of going from an AI model to a working production application. It covers questions like: when and how to use techniques like RAG (Retrieval-Augmented Generation — enriching an AI's answers with relevant external documents), how to detect and reduce hallucinations (false or made-up outputs), when to fine-tune a model (customize it on your own data), how to evaluate AI outputs, and how to make AI systems faster and cheaper to run.

The target audience includes AI engineers, machine learning engineers, data scientists, engineering managers, and technical product managers who want a framework for building serious AI products rather than just demos. The repository includes a Jupyter Notebook (an interactive coding document) for generating conversation heatmaps from ChatGPT and Claude chat histories. The full README is longer than what was provided.