aie-book

This repository is a companion resource for the book AI Engineering by Chip Huyen and is marked as work in progress, with more materials expected. Available materials include a table of contents, chapter summaries, study notes, a general AI engineering resource list, prompt examples, case studies, notes on AI misalignment, and appendix material. It also includes a Jupyter notebook for generating heatmaps from ChatGPT and Claude conversations. The book focuses on the end-to-end process of adapting foundation models, including large language models and large multimodal models, for real-world applications. It is positioned as a fundamentals-and-decision-framework resource rather than a tool-specific tutorial, and the README notes that it contains limited code. Topics covered include application evaluation, hallucination detection and mitigation, prompt engineering, retrieval-augmented generation, agents, when to use or avoid fine-tuning, data requirements and quality, latency and cost optimization, security, and feedback loops for continued improvement. The intended audience includes AI engineers, ML engineers, data scientists, engineering managers, technical product managers, tool developers, researchers, and people exploring AI engineering careers. The repository also links to purchase options, translated editions, and a citation for the book.