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Here's your opportunity to catch up on Manning's latest releases, MEAP updates, bestsellers and more! And don't forget: you always get the best deals at manning.com!
New MEAP! Lean Software Engineering
Fix the system, not the code
It's never been easier to generate high-quality code quickly. Most delay, waste, and fragility in software development persists because end-to-end delivery systems are burdened with unnecessary steps, complex infrastructure, and needless ceremony. Lean Software Engineering: Fix the system, not the code introduces an AI-aware systems thinking approach adapted for the modern software development lifecycle, targeting the bottlenecks where high-value improvements live.
In the late 1990s, the "Lean" philosophy migrated from industrial manufacturing to software development with the promise of maximizing business value while continuously eliminating process waste. Many Lean-inspired delivery systems emphasize automated testing, iterative review, and other code-centric approaches to software quality. In this book, author Leigh Griffin demonstrates how Lean thinking can shape quality, operational cost, and long-term maintainability in a workflow that includes coding agents and other modern tools. Instantly familiar concrete examples ground each concept, including pull request reviews, debugging scenarios, and CI/CD workflows that mirror real-world engineering practice. [Read more]
3 chapters of this new MEAP are available now with more to follow soon!
New MEAP! Retrieval Augmented Generation, The Seminal Papers
Principles for architecting reliable and verifiable AI
Retrieval Augmented Generation (RAG) is a standard process for grounding LLM prompts in user-specified content rather than relying only on a model's training data. RAG has grown from a simple prompt engineering workflow into a sophisticated set of data analysis, storage, and retrieval techniques. Retrieval Augmented Generation, The Seminal Papers explores 12 foundational research papers that explain why RAG works, how it's built, and what makes it different from other approaches.
This authoritative book explores the papers that define RAG's enduring architectural pattern. Author Ben Auffarth traces RAG's evolution from the foundational breakthroughs of REALM, RAG, and DPR to advanced architectures like FiD and Atlas. Designed to be both interesting and practical, Retrieval Augmented Generation, The Seminal Papers illuminates techniques that empower systems to retrieve intelligently, evaluate themselves, and recover from errors. Over 40 code samples, architectural diagrams, and industry case studies make each concept easy to understand. As you master the patterns behind RAG, you'll better understand tradeoffs, diagnose failures, and effectively evaluate and improve your own RAG implementations. [Read more]
5 chapters of this new MEAP are available now with more to follow soon!
This book teaches you to design reliable LLM-powered systems by focusing on the concepts, architectures, and design patterns that will stay stable even as models and APIs change. You'll learn to structure prompts, compose modular chains, and build RAG pipelines that ingest documents, split them into chunks, embed them, retrieve the right context, and ground answers to eliminate (or vastly reduce) hallucinations.
Along the way you'll build concrete applications—
summarization and Q&A engines, context-aware chatbots with memory, and tool-using AI agents that orchestrate multi-step workflows with branching logic. For the examples, the book uses Python, LangChain, LangGraph, and LangSmith, but you'll be able to generalize to other frameworks. You'll understand with clarity and confidence how to keep integrations maintainable, manage context limits and cost/latency tradeoffs, and evaluate, debug, and monitor behavior so your systems work in production. [Read more]
Expires midnight PT on March 8th. Only at manning.com.
Note: Final discount will be applied in cart. For products already on sale, the best available discount will be applied.
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