Editor's top Prompt Engineering books
1Prompt Engineering for LLMs
John Berryman, Albert Ziegler · O'Reilly · 282 pages · ~7 hrs to read
The most thorough book on prompt engineering techniques — covers task formulation, in-context learning, chain-of-thought, and building reliable prompts for production systems with practical code examples.
Prompt Engineering Books for Beginners
2Hands-On Large Language Models
Jay Alammar, Maarten Grootendorst · O'Reilly · 449 pages · ~11 hrs to read
The clearest illustrated path from "what is a token" to production LLM applications — Alammar's visual explanations (the same style behind his famous Illustrated Transformer) make attention, embeddings, and prompting mechanics intuitive rather than abstract.
Co-Intelligence: Living and Working with AI
Ethan Mollick · Portfolio · 257 pages · ~6 hrs to read
Not a technical prompting manual — a Wharton professor's field guide to treating AI as a co-worker, with concrete rules of thumb (always invite it to the table, treat it as a person of variable expertise) that translate directly into better prompt habits for non-engineers.
Intermediate & Advanced Prompt Engineering Books
5Prompt Engineering for LLMs
John Berryman, Albert Ziegler · O'Reilly · 282 pages · ~7 hrs to read
The most thorough book on prompt engineering techniques — covers task formulation, in-context learning, chain-of-thought, and building reliable prompts for production systems with practical code examples.
AI Engineering
Chip Huyen · O'Reilly · 535 pages · ~13 hrs to read
Covers prompt engineering as part of the full AI application engineering stack — including evaluation, context management, and the trade-offs between prompting and fine-tuning. The most complete guide to production AI engineering.
Prompt Engineering for Generative AI
James Phoenix, Mike Taylor · O'Reilly · 430 pages · ~11 hrs to read
Goes beyond prompt templates into how requests actually get transformed into document-completion problems inside the model — covers text, image, and code generation with the same underlying framework. A stronger theoretical grounding than most prompting books.
Quick Start Guide to Large Language Models, 2nd Edition
Sinan Ozdemir · Addison-Wesley · 584 pages · ~15 hrs to read
Practical strategies for prompting, embeddings, fine-tuning, and multimodal AI side by side, with runnable code — useful for engineers who want to see where prompt engineering stops and fine-tuning or RAG should take over.
Generative AI with LangChain, 2nd Edition
Ben Auffarth, Leonid Kuligin · Packt · 485 pages · ~12 hrs to read
Prompt design in the context of real agent and RAG pipelines rather than isolated examples — the 2nd edition's focus on LangGraph workflows and multi-agent architectures shows how prompts hold up (or fall apart) once chained into a system.
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