Somewhere in the past year, ChatGPT has gone from "cool, interesting, amusing" to a massively valuable work assistant capable of writing Python scripts, analysing data, and doing lots, lots, more. The key to this? The rapid evolution of OpenAI's GPT models and making my first forays into prompt engineering.

If I thought I was getting good, though, this book took me reminded me that I'm just scratching the surface. Halfway through the first chapter I was already furiously scribbling notes in the margins for what I could do better with my prompt writing and by the end of the text I felt like I had gotten a very good grounding - not just in GPTs specifically but in the bigger picture of how these hugely powerful tools were trained and came to maturity.

I imagine that few will argue with my assertion that there is lots of hyperbole and "noise" in the AI space right now which, as ever, makes it hard to pick out the signal from the noise. Which is precisely why I sought out an O'Reilly title and I'm very glad that I did.

Thorough, excellent, and I hope that this edition will be the first of many. As this rapidly maturing field scales and matures I think that prompt engineering will be an essential discipline to master. Pick up this text to get a good foothold on things.

Prompt engineering is the art and science of finding the right words to generate the right responses from artificial intelligence (AI). It's becoming a skill in-demand in today's workplaces. It's also becoming an essential skill for life. To understand prompt engineering, you must understand how AI tools understand their inputs. This book explains that to you in many forms.

It covers prompting as it intersects all the major AI disciplines, like general prompts (as in a ChatBot), fine-tuning, and retrieval-augmented generation (RAG). It also introduces how prompting intersects a couple of image-generation tools.

As a scientist, I appreciate the theoretical approach to these practical matters. Too many people are hacks at AI these days, and any technical understanding can rapidly advance an individual's effectiveness. Prompt engineering is often made fun of as a "soft" topic, but as this book demonstrates, it intersects all the major AI areas. Presumably less garbage in means less garbage out. This book shows how you can make that take place.

As typical for O'Reilly materials, this book appeals to people who desire an intermediate-to-advanced understanding of how AI works. It's not for the casual user. Anyone technical involved in professional knowledge generation using AI can benefit from understanding the dynamics "under the hood." It's a good, though perhaps not ground-breaking, textbook for those of us unable to take a class in the subject. Prompt engineering may be a soft topic to many, but books like this ground the field in the science that can make or break a digital or software product.

Great book! It is helpful as I work towards my Masters of Science in Applied Artificial Intelligence

This is a solid book for understanding the art and science of working with LLMs and other generative AI models. I always struggled with getting the output I was looking for, and wasn't sure how best to "ask" the models for what I wanted. This book did a great job of laying out the strategies and practical guidance to craft the prompts. There were a lot of tips and tricks, but the overall understanding and framework around prompt engineering has been super useful.

Hands down, the best book on prompt engineering and implementing LLMs. Really enjoyed Michael and James deep dive. Whether you're technical or not, this book is foundational to a deeper understanding in how to properly explore and implement LLMs.

I bought a new book. But heavy damage in cover of book. Not good.

I applaud the authors for putting forth a comprehensive introduction in a rapidly evolving space. I absorbed a lot, helpful as I was developing a prototype — using open source methods.

And that’s where I was disappointed. The LLM and examples are highly adapted to OpenAI’s GPT-x and the bulky LangChain framework, something not obvious until you dig in to the book. Sure, this may be where newbie demand was when the authors began writing. But as the open source models and OpenAI alternatives gain speed (e.g. Llama 3.1, Groq, etc.) this book may quickly need an updated and expanded version to stay relevant.

Some helpful prompt frameworks, but parts felt repetitive and a few sections stayed too high-level for advanced users. Beginners will likely benefit more than experienced practitioners. If you’re new to prompt engineering it’s a decent starting point; if you’re already building structured prompts daily, it may feel light.

The book is ok yet I think you would get more for less if you just google for docs and articles on the web

Brilliant

Great book! I am using it in conjunction with the authors training course.

This book on prompt engineering is an absolute gem! As someone delving into the intricacies of AI and language models, I found this resource incredibly valuable. The author does a fantastic job of breaking down complex concepts into manageable, easy-to-understand sections.

The practical advice is where this book truly shines. Each chapter is filled with real-world examples and step-by-step guides that make applying the techniques straightforward. Whether you're a novice just starting out or a seasoned professional looking to refine your skills, there's something here for everyone.

Gives a thorough introduction to prompt engineering . Some Python coding skills required