Trustworthy Generative AI bundle 
Your next AI project will need more than one kind of expertise. Bring four complementary perspectives to your work: how generative AI is misused, how to check its claims, how to control agent behavior, and how to manage an LLM service. With this complete collection, you can study each area in depth and return to the books when new testing, design, or operational questions arise. Get all four ebooks for $99.99!
LLM Evaluation and Alignment, The Foundational Ideas 
It’s a fundamental truth that all software—even AI systems—is broken. AI engineers who can diagnose faults and refine systems to align with business needs are in high demand. LLM Evaluation and Alignment, The Foundational Ideas expands the foundational research into judging and adapting AI systems into a collection of practical techniques you can use on the job. As you trace the progression from surface-level text matching to semantic similarity to judgment-based evaluation, you’ll build the mental models necessary to choose the right metrics, detect failure modes, and close the loop from evaluation to alignment.LLM Evaluation and Alignment, The Foundational Ideas teaches you to think of evaluation as a design constraint. You’ll employ a "working backwards" methodology that begins with what your system must get right, which directs you to the appropriate evaluation approach. As you internalize the define > evaluate > analysis > align cycle, you’ll start making more informed tradeoffs and expertly balancing helpfulness, safety, and brand voice in your models.
Introduction to Generative AI, Second Edition
Introduction to Generative AI, Second Edition is a completely revised and updated guide to the capabilities, risks, and limitations of generative AI. You’ll understand the latest innovations in AI, AI agents, multimodal training, reasoning models, retrieval-augmented generation (RAG), and more. Along the way, you’ll explore how AI is impacting the world, with an expert-level look at AI in industry, education, and society.
Agent Design Patterns
AI agents are showing up everywhere—and most of them are being built by trial and error. Agent Design Patterns distills the experience of a growing community of agent builders into 20+ composable, reusable patterns for building AI agents that are reliable, efficient, controllable, and easy to reason about. In this uniquely valuable book, author and NVIDIA Research scientist Peter Belcak gives you a durable engineering vocabulary and design intuition that outlasts any new model release.Each pattern included here is production tested and designed to click together as you construct transparent, testable, deployment-ready agentic applications. You’ll appreciate the familiar presentation style, with a simple template of a named problem, a clear solution, benefits, drawbacks, popular variants, and rules for composition with other patterns. Informative diagrams, worked examples, and Belcak’s clear mathematician-turned-engineer voice make even the most subtle patterns easy to internalize.
By the end, you’ll be able to read an underperforming agent, pinpoint the exact quality that is lacking, and reach for the specific pattern that addresses it. You’ll lower per-run costs without redesigning your agent, and even build self-improving agents that auto-tune their own prompts.
LLMs in Production
LLMs in Production teaches you how to develop an LLMOps plan that can take an AI app smoothly from design to delivery. You’ll learn techniques for preparing an LLM dataset, cost-efficient training hacks like LORA and RLHF, and industry benchmarks for model evaluation. Along the way, you’ll put your new skills to use in three exciting example projects: creating and training a custom LLM, building a VSCode AI coding extension, and deploying a small model to a Raspberry Pi.
Some bundled books and liveVideos are part of the Manning Early Access Program. You'll get all the available content now, new content as it's created, and the final product when it's ready.
