Books

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.

The first thing many people hit with an AI coding assistant is a plateau. A correction made on Monday is gone by Thursday. This book is about the operating model above the prompt, where truth lives, how a correction becomes a standing rule that holds, and which judgments stay in human hands.

Build real-world web applications faster with Claude Code by your side. This hands-on guide takes you from web development fundamentals to production-ready full-stack engineering with React, Next.js, TypeScript and PostgreSQL. Learn practical AI-assisted workflows while building, testing, securing and deploying applications that are ready for real users.

Envoy Proxy is the foundation of modern cloud-native networking, powering service meshes, API gateways and AI infrastructure. This practical guide shows you how to design, deploy and operate Envoy in production with expert guidance, real-world configurations and advanced patterns for scalable, resilient systems.

Enterprise AI is more than LLMs and chatbots. Learn how to design secure, scalable, and production-ready AI systems using a vendor-neutral architecture that connects data, models, agents, APIs, governance, and enterprise integration into one modern AI stack.

Build AI agents that do real work with the Google Agent Development Kit (ADK), Python, and Google Cloud. Through complete, runnable examples, you'll learn how to build, orchestrate, and deploy production-ready multi-agent systems with practical skills you can apply from day one.

Build AI agents that do more than generate text. This book shows you how to use the Claude Agent SDK to create autonomous systems that use tools, manage context, coordinate multiple agents, and solve complex tasks. With practical examples in Python and TypeScript, you will learn how to build secure, scalable agents ready for production.

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.

This practical guide shows you how to build production-ready speech recognition applications from the ground up. Learn how to use Voice Activity Detection, choose the right ASR models, build real-time inference pipelines, and deploy scalable systems with hands-on examples and modern open-source tools.

MCP is the protocol powering the next generation of AI agents, and this is the only book that teaches you all of it. From Python fundamentals to low-level SSE transport, go from zero to production-ready MCP developer.

How should an AI system make decisions when information is incomplete?How can machines quantify uncertainty instead of merely producing predictions?How can intelligent systems continuously update their beliefs as new evidence emerges?The answer lies in Bayesian Mathematics.In Bayesian Mathematics for AI Decision Making, Anshuman Mishra explores the powerful framework that enables modern AI systems to reason probabilistically, model uncertainty, and make rational decisions in complex environments.From Bayesian inference and probabilistic programming to uncertainty-aware deep learning, reinforcement learning, healthcare diagnostics, robotics, and financial forecasting, this book reveals how Bayesian thinking is shaping the next generation of Artificial Intelligence.Learn how uncertainty becomes knowledge—and how probability becomes intelligence.

Your agent passed every load test and timed out in production anyway. This free practitioner's guide shows why the traditional performance playbook breaks for agentic AI, and what replaces it: latency budgets, bounded autonomy, token SLOs, and production-grade observability, from a performance engineering and observability architect with two decades in production.

A hands-on guide to designing, building, testing, and deploying secure stdio and SSE MCP servers in Python and TypeScript (447 manuscript pages).

Master Codex CLI from your first prompt to production-ready AI workflows. Learn how to automate coding, streamline development, and use OpenAI's terminal-native coding agent with confidence.

Build smarter AI systems that go beyond the limits of large language models. Retrieval-Augmented Generation is a practical guide to designing, implementing, and scaling RAG applications with modern retrieval techniques, vector databases, and real-world deployment strategies.