AI Engineering: Building Applications with Foundation Models

Received new book

The shipment received really damaged

The central idea of the book is that foundation models have become so powerful and expensive to build that, instead of training models, many organizations might be better off creating applications on top of them. The book covers evaluation, guardrails, security, finetuning, context construction, inference optimization, user feedback and architecture. The level of detail is excellent: we're looking under the hood just enough to understand what's going on, but keep that high level perspective that allows the book to give a overview of a broad topic in just 500 pages. I highly recommended this book to engineers looking for an overview of AI engineering — as opposed to ML engineering, which might be too low-level for them and be more relevant for data scientists.

All words and no substance - not even a single diagram or flowchart to illustrate a process - to call it 'engineering' completely misses the point.

Best book on AI engineering. It is not based on technologies, but on principles and patterns. It is a MUST if you start with agents development or if you just want to know about AI topics.

This book is so incredibly well-organized and well-edited that it’s hard to believe it’s a first edition rather than a third or fourth. I love when authors invite readers to jump around and read chapters out of order; in this case, every section proved helpful. This book offers a clear and valuable overview of AI, I plan to keep it close at hand as a reference.

Muito bom o livro, ainda não terminei mas possui varios insights sobre AI