Agentic Engineering

面向智能体重度用户的实战可靠性手册：不教造智能体、不教提示词技巧、不做产品测评； 每天用智能体 2 小时以上、已配多个工具、需要一套可预算 / 可监控 / 可验收的运营方法的实践者；

ChatGPT can save you time, sharpen your ideas and change the way you work, but only if you know how to use it well. This practical guide takes you from your first prompt to advanced techniques, with real-world examples for writing, research, coding, business and creativity. Learn what works, what doesn’t and how to get better results every day.

Vectors, embeddings, retrieval, agents, and evaluation are all built from first principles inside the chapter that needs them. No mathematics. No machine learning background. No prior AI experience and no framework knowledge is required. We build with plain Python and small, single-purpose libraries.  

What if your AI didn’t just answer questions—but solved problems?Imagine an AI that doesn’t just chat—it plans, reasons, and takes action. An AI that can fetch data, run diagnostics, collaborate with other agents, and even handle your most tedious tasks—all while you focus on what matters.Google’s Agent Development Kit (ADK) makes this possible,

Build smarter AI applications with Redis at the core. This practical guide shows you how to use vector search, RAG, semantic caching, agent memory and real-time inference to create fast, scalable systems. With runnable Python examples throughout, you’ll learn how to take AI projects from prototype to production.

当 AI 能替你写代码，真正的危险不是它写错，而是你以为它不会错。

Unlock the full potential of Qwen 3.8 with a practical guide built for real results. Learn the techniques behind stronger prompts, avoid common mistakes, and create reliable outputs for coding, research, business, creative projects and AI agents with clear examples you can use right away.

You're half right about the slop. Here's how to make Claude Code leverage without lowering your standards.

Everyone talks about large language models. Very few actually understand the machine.Whoever you are in the room — the one being asked, or the one deciding — this book puts you on the side of the conversation that understands the machinery.

Turn AI-generated code into production software. Use observable requirements, architectural boundaries, TDD, review, release gates, security, payment, delivery, and operations to ship maintainable AI-assisted systems.

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.

A working engineer's guide to building and maintaining production software with autonomous terminal coding agents (382 manuscript pages).

AI coding agents can write code fast, but they need codebases built for collaboration. This book shows experienced engineers how to design, test and maintain software that works seamlessly with tools like Copilot, Cursor and Claude Code. Practical patterns, real projects and proven workflows help you build systems that scale with AI.

AI agents become truly powerful when they can reason, adapt and recover instead of following a fixed sequence of steps. This book shows you how to design intelligent agent systems with computational graphs, giving you the tools to build scalable, reliable applications that can handle real-world complexity with confidence.

Your pilot went well. That was never the question. In a regulated industry, an AI system is acceptable only when it can prove what it did: which source it used, what stopped it acting, why it decided as it did eleven months ago. A field guide for the executives who have to sign.