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Essential Agentic AI Engineering: How to Deploy autonomous agents that proactively plan, reason, and act to achieve complex goals with little human supervision
You don’t need another toy demo—you need agentic AI that ships, scales, and doesn’t break at 2 a.m.
This book shows you how to design, build, and operate autonomous AI agents that plan, reason, and act reliably—with minimal supervision. You’ll move from slideware to systems you can deploy.
Inside, you’ll work through runnable labs and reproducible a research agent, a coding agent, and a multi-agent planner. You’ll learn long-term memory architectures (vector DBs, episodic + semantic stores), evaluation frameworks (how to benchmark agents and reproduce results), and the safety playbook for real systems (prompt-injection defenses, permissions, audit trails, governance). You’ll also get “debugging an agent” walkthroughs—step-by-step sessions where we instrument, probe, and fix brittle behavior—plus abstraction-level lessons distilled from how leaders at Amazon, GitHub, and Anthropic approach agents (no NDAs required). Cap it off with the Agent Lifecycle Framework—Design → Build → Test → Deploy → Monitor → Evolve—so your first launch isn’t your last.
If you’re ready to move past prototypes and own production reliability, start building with Agentic AI Engineering today.
This book shows you how to design, build, and operate autonomous AI agents that plan, reason, and act reliably—with minimal supervision. You’ll move from slideware to systems you can deploy.
Inside, you’ll work through runnable labs and reproducible a research agent, a coding agent, and a multi-agent planner. You’ll learn long-term memory architectures (vector DBs, episodic + semantic stores), evaluation frameworks (how to benchmark agents and reproduce results), and the safety playbook for real systems (prompt-injection defenses, permissions, audit trails, governance). You’ll also get “debugging an agent” walkthroughs—step-by-step sessions where we instrument, probe, and fix brittle behavior—plus abstraction-level lessons distilled from how leaders at Amazon, GitHub, and Anthropic approach agents (no NDAs required). Cap it off with the Agent Lifecycle Framework—Design → Build → Test → Deploy → Monitor → Evolve—so your first launch isn’t your last.
If you’re ready to move past prototypes and own production reliability, start building with Agentic AI Engineering today.
333 pages, Kindle Edition
Published September 28, 2025
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