Books

The Codex Playbook helps enterprise engineering teams turn Codex from a helpful assistant into a reliable part of the software delivery system, with practical patterns for context engineering, repositories, GitHub workflows, MCP, governance, and AI-assisted development.

Local Intelligence shows you how to run large language models entirely on your Mac with Apple Silicon. Learn to use tools like Ollama, MLX, and llama.cpp, understand quantization, and build real local AI applications with open-source code.

AI的边界，就是你的方向。从大模型的底层命门，推导出你不可替代的理由。

You shipped the demo. The model worked. Now production is coming, and the demo is not a system. An agentic system is a distributed-systems engineering problem — the reliability lives in the shell, not the model.

Discover the mathematics powering the future of Artificial Intelligence and cybersecurity.Algebraic Foundations of AI: Groups, Rings, and Fields in Security & Cryptography reveals how abstract algebra forms the backbone of modern AI security, cryptographic systems, blockchain technologies, privacy-preserving machine learning, federated learning, and post-quantum cryptography.

A hands-on guide to designing, building, testing, and deploying secure stdio and SSE MCP servers in Python and TypeScript (437 manuscript pages).

Learn how large language models work instead of relying on black-box APIs. Building Large Language Models from Scratch takes you through training a Transformer model in PyTorch, from raw text to a working inference API, covering tokenization, attention, distributed training, and alignment along the way.

LLMs are too big for single GPUs, but quantization fixes that. This book cuts through the hype to show you how to actually compress models using GPTQ, AWQ, GGUF, and NF4 without losing quality. You get real benchmarks, working code, and a clear way to pick the right tool for your hardware. Stop guessing and start deploying efficient models today.

AI-collaboration interviews are not about prompting better. They are about controlling the process. Learn a four-step framework to ask better questions, write a clear spec, guide AI-assisted building, and prove correctness with independent review and tests.

Den praktiska AI-guiden på svenska. För dig som vill använda AI i vardagen utan att vara tekniker. Med ett 30-dagarsprogram, konkreta promptar och enkla förklaringar tar boken dig från nybörjare till trygg AI-användare på 30 dagar.

Unlock the full potential of Claude Fable 5 with a practical guide built for developers who are shipping real AI applications. From prompt engineering and agent orchestration to RAG, memory, safety, evaluation, and production deployment, this definitive reference delivers proven patterns, hands-on examples, and reusable templates to help you build reliable, scalable AI systems with confidence.

Linear Programming and AI Optimization Models (VOL-3) delivers practical mastery in scheduling, supply chain, logistics, hybrid AI-OR systems, large-scale cloud optimization, and emerging technologies. With Python implementations, industry case studies, and forward-looking research trends, this volume turns theory into powerful real-world solutions.

Take your optimization skills to the next level with AI.Linear Programming and AI Optimization Models (VOL-2) dives deep into the algorithms driving modern Machine Learning and Intelligent Systems. Master Gradient Descent, Adam, Reinforcement Learning, Genetic Algorithms, Particle Swarm Optimization, Constraint Satisfaction, and advanced Network Models.

Unlock the power of optimization in the age of AI."Linear Programming and AI Optimization Models" delivers a masterful blend of classical Operations Research and modern Machine Learning applications. From the elegant Simplex Method to advanced decomposition techniques and KKT conditions, this Volume-1 builds a rock-solid foundation while demonstrating how these powerful algorithms .