Designing AI Agents (MEAP 1) by Jia Huang (.ePUB)+
File Size: 14.5 MB
Designing AI Agents: Principles, patterns, and best practices (MEAP 1) by Jia Huang
Requirements: .ePUB, .PDF reader, 14.5 MB
Overview: AI agents promise to automate work on an unprecedented scale—even for tasks requiring reasoning and complex multi-step processes. In Designing AI Agents, you’ll learn how to establish agent architectures that manage costs and take governance seriously from day one. This innovative book explores 27 reusable patterns that you can apply to your own agentic systems confidently. Each pattern has been stress-tested at scale, with over 10,000 engineers applying them to ship production agents in banks, manufacturers, and AI startups. You’ll appreciate how this book guides you toward system and harness design that imposes certainty and reliability on the non-deterministic behavior of LLM-driven agents. Unlike other “agentic patterns” books that dwell on abstract theory, every chapter in this practical guide grows a single running example. You’ll incrementally build Argus, a code-review agent that evolves from a 50-line reasoning-and-action loop all the way to a production-grade system. As you steadily upgrade Argus, you’ll learn both which patterns to use and when and why to apply them. Plus, full case studies exploring agents working as a DevOps incident responder, compliance reviewer, and research synthesis agent show the methodology in action across diverse domains. For engineers who know the basics of agent design and want to deliver reliable, cost-effective agentic AI. To get the most out of these chapters, you’ll want working knowledge of Python, basic familiarity with at least one LLM API (Claude, GPT, or Gemini), and the kind of skepticism a good engineer brings to anything new. You don’t need to have shipped a multi-agent system. You need to want to ship one that works.
Genre: Non-Fiction > Tech & Devices
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