Books

As AI models become increasingly accessible, the real challenge lies in making them work reliably in production. Advanced Harness Design explores the engineering behind robust AI systems, from architecture and orchestration to security and operations. Discover the patterns, tools and practical techniques needed to build dependable AI systems that perform in the real world.

Build a real LLM inference engine from the ground up in portable C. Learn how transformers work, load SafeTensors weights, implement KV caching and optimize inference on the CPU. By the end, you will run TinyLlama locally and generate text with a complete working runtime.

What does it take to run an LLM on hardware that barely has enough memory to breathe? This practical guide takes you from transformer math and model compression to inference runtimes, benchmarking and real-world deployment, with hands-on case studies for building fully offline LLM systems on tiny devices.

Take a practical journey through SGLang, from its core architecture to real-world deployment and optimization. Built for engineers who need to run LLM inference reliably at scale, this handbook breaks down the tools, techniques and operational know-how needed to build and maintain production-ready SGLang systems.

Learn to build production-ready LLM applications with DSPy through hands-on tutorials, complete runnable examples, and real-world projects. Master DSPy's core abstractions and create AI systems that improve with data instead of endless prompt tweaking.

Learn how to build reliable AI agents with PydanticAI, from simple chatbots to production-ready multi-agent systems. With practical examples, clear explanations, and hands-on projects, this book helps you write AI applications that are structured, testable, and easy to maintain.

 What You Will Learn1. Foundations of Creative WritingYou will explore the essential building blocks of storytelling, including plot development, character creation, dialogue writing, and narrative techniques.2. AI Tools and Prompt EngineeringThe book introduces you to modern AI writing tools and teaches you how to use them effectively through structured prompts and iterative refinement.3. Writing Different FormatsYou will learn how to create:Novels with strong plot and character arcsScreenplays with professional formattingPoetry with emotional depth and rhythmEngaging storytelling content across genres4. Editing and Quality ControlThe book emphasizes the importance of human editing, ensuring your work is polished, original, and aligned with professional standards.5. Publishing and MarketingA dedicated section guides you through publishing your work on platforms like Amazon KDP, including formatting, keywords, and marketing strategies.  Ethical and Responsible Use of AIOne of the most important aspects of this book is its focus on ethical writing. AI is a powerful tool, but it must be used responsibly. The book discusses:Avoiding plagiarismUnderstanding copyright ownershipMaintaining transparencyEnsuring originalityThis ensures that your work remains authentic and compliant with global publishing standards.  Who Should Read This Book?This book is ideal for:Students (BCA, MCA, BTech, and other disciplines)Aspiring authors and storytellersContent creators and bloggersScriptwriters and poetsEducators and researchersFreelancers and digital marketersNo prior experience with AI is required. The book starts from basics and gradually moves to advanced concepts.

Design, Build, and Operate Autonomous AI Systems for Modern Cyber DefenseCybersecurity is evolving beyond traditional automation toward intelligent systems capable of continuously analyzing security telemetry, investigating threats, coordinating specialized tools, and executing controlled defensive actions. This shift introduces new engineering challenges involving agent architecture, decision-making, authorization, operational reliability, and the verification of security-critical actions.

Bestselling book on building LLMs. A practical, project-driven manual for engineers who want to understand how modern language models are built — and where they fail — by writing every layer themselves. From a scalar autograd engine to RLHF to fused specialists, in 36 hands-on projects with deliberate sabotage experiments. Build it. Break it. Measure it.

Building fast LLM inference is about far more than turning the right knobs. This book takes you inside vLLM and the systems behind it, showing how memory, scheduling, GPUs and distributed serving shape real-world performance. Learn how to measure what matters, find bottlenecks and build inference infrastructure that scales without wasting money.

AI coding agents can move fast, but speed without clear intent creates expensive mistakes. This practical guide shows how Behavior-Driven Development turns specifications into a reliable contract between you and autonomous coding systems, helping agents build the right thing, catch problems earlier and produce software you can trust.

AI agents don’t fail because they forget everything. They fail because they remember badly. This book shows you how to engineer memory that stays accurate, efficient and useful over time. From SQLite and PostgreSQL to vector indexes and multi-agent systems, you’ll learn what it takes to build agents that can run for days without losing the plot.

Build Model Context Protocol servers that go beyond demos. This hands-on guide walks you from the fundamentals to production deployment with practical examples in Python, TypeScript, Go, Rust and Java. Learn the patterns, tools and real-world practices needed to build secure, scalable MCP servers that are ready for enterprise AI.

Build powerful AI agents that run entirely on your own hardware with Ollama. Learn practical patterns for RAG, multi-agent systems, security and deployment through clear explanations and production-ready code you can use right away. From first setup to reliable real-world applications, this book helps you build with confidence.

AI can generate code in seconds, but shipping production-grade software requires far more than fast prompts. Vibe Engineering shows you how to work with AI coding assistants to build systems that are reliable, secure, and maintainable. Through practical examples and proven workflows, you will learn how to turn AI from a code generator into a trusted engineering partner.