ManningBooks

ManningBooks

Devtalk Sponsor

Context Engineering (Manning)

Context engineering is the discipline of selecting, organizing, updating, compressing, prioritizing the precise context a model needs to generate accurate responses. This book shows you how to combine well-designed prompts with smart search, content filtering, and advanced RAG techniques incorporating many types of stored data to create reliable responses in your AI applications.

Boni Garcia

If you’re building with LLMs, you’ve probably run into the same pattern many teams are seeing: a clever prompt works in a demo, then falls apart when the system has to handle fresh data, long conversations, tools, memory, multiple steps, or production constraints. The missing piece is often context: what the model sees, when it sees it, how that context is selected, and what gets left out.

Context Engineering treats that as a software design problem.

The book shows how to build AI systems where the model’s information environment is designed with the same care as the code around it. Boni García covers the full context stack: instructions, external knowledge, tools, memory, state, user prompts, orchestration, evaluation, observability, and governance.

Early chapters are already available and cover:

  • What context engineering is and why prompt engineering is only one part of the picture

  • How LLM-based systems evolve from single model calls to workflows, agents, and agentic systems

  • System prompts, agent skills, and instruction artifacts such as AGENTS.md and CLAUDE.md

  • RAG pipelines, chunking, vector databases, graph RAG, hybrid RAG, agentic RAG, vectorless RAG, cache-augmented generation, and context stuffing

  • Tool use through function calling, command-line interfaces, and the Model Context Protocol

The hands-on sections use current tools and platforms, including OpenAI, Anthropic Claude, Google Gemini, Ollama, LangChain, LlamaIndex, CrewAI, DSPy, RAGFlow, and MCP servers. Examples are grounded in working code, with a companion GitHub repository for readers who want to follow along.

This book is aimed at AI engineers, data scientists, and engineering managers who already know the basics of LLMs and agents and want to build systems that behave more consistently outside a notebook or prototype.

A bit about the author: Boni García is an Associate Professor at Universidad Carlos III de Madrid, a Selenium project tech lead, and the creator and maintainer of WebDriverManager and Selenium Manager. His work sits at the intersection of software engineering, test automation, and applied AI.

MEAP means you can start reading now while the book is still being completed. You’ll get updates as new chapters are added.

If you’re working on RAG, agents, coding assistants, enterprise copilots, or any LLM system where “just make the prompt better” has stopped being enough, this one should be on your list.


Don’t forget you can get 45% off with your Devtalk discount! Just use the coupon code “devtalk.com” at checkout :+1:

First Post!

KnowledgeIsPower

KnowledgeIsPower

Looks like a very good book.

I just tried to implement a POC on RAG / chatbot without much domain knowledge on it.

Where Next?

Popular Ai topics Top

ManningBooks
Before deploying an AI model into production, you need to know more than just its accuracy. Will it be fast enough for your users? Will i...
New
New
ManningBooks
Grokking AI Algorithms, Second Edition introduces the most important AI algorithms using relatable illustrations, interesting examples, a...
New
ManningBooks
The bestselling book on Python deep learning, now covering generative AI, Keras 3, PyTorch, and JAX! François Chollet and Matthew ...
New
ManningBooks
Erlang and OTP in Action teaches you the concepts of concurrent programming and the use of Erlang’s message-passing model. It walks you t...
New
ManningBooks
Hugging Face in Action reveals how to get the absolute best out of everything Hugging Face, from accessing state-of-the-art models to bui...
New
ManningBooks
Today’s AI models demand a lot of memory, compute, and server horsepower–which quickly translates into cost. Quantization and Fast Infere...
New
smarties-press
Bertrand Meyer The most important technology of our time — decoded Millions use AI every day. Few understand why it works. ✓ Why large ...
New
ManningBooks
Until recently, writing GPU kernels for LLM training and inference meant learning low-level programming tools like CUDA and C++. Triton, ...
New
ManningBooks
The Claude suite of LLM-powered tools and agents from Anthropic has radiacally–and permanently–changed the way technical professionals de...
New

Other popular topics Top

New
Margaret
Hello everyone! This thread is to tell you about what authors from The Pragmatic Bookshelf are writing on Medium.
1147 29994 760
New
Maartz
Hi folks, I don’t know if I saw this here but, here’s a new programming language, called Roc Reminds me a bit of Elm and thus Haskell. ...
New
PragmaticBookshelf
Rails 7 completely redefines what it means to produce fantastic user experiences and provides a way to achieve all the benefits of single...
New
PragmaticBookshelf
Build efficient applications that exploit the unique benefits of a pure functional language, learning from an engineer who uses Haskell t...
New
New
DevotionGeo
I have always used antique keyboards like Cherry MX 1800 or Cherry MX 8100 and almost always have modified the switches in some way, like...
New
CommunityNews
A Brief Review of the Minisforum V3 AMD Tablet. Update: I have created an awesome-minisforum-v3 GitHub repository to list information fo...
New
AstonJ
If you’re getting errors like this: psql: error: connection to server on socket “/tmp/.s.PGSQL.5432” failed: No such file or directory ...
New
PragmaticBookshelf
Get the comprehensive, insider information you need for Rails 8 with the new edition of this award-winning classic. Sam Ruby @rubys ...
New