AI Engineering versus Building Agentic AI Systems.
Both show up on every "best" list. They're not competitors. They're a sequence. Here's which one to read first, and when.
Reviewed by Ashish Sheth · Updated April 2026
Author
Chip Huyen
Anjanava Biswas, Wrick Talukdar
Pages
532
286
Published
2025
2025
Publisher
O'Reilly Media
Packt Publishing
Level
intermediate
intermediate
Amazon Rating
4.4/5 (899)
4/5 (69)
Goodreads Rating
4.4/5 (1,061)
2.93/5 (27)
AI Engineering
Strengths
+ Clear, accessible explanations of complex AI/ML concepts
+ Practical and implementation-focused rather than theoretical
+ Well-researched with extensive references to current literature
+ Excellent for software engineers transitioning into AI development
Caveats
− Inconsistent depth: some topics feel surface-level for experienced practitioners
− Limited practical code examples
− Breadth-first approach means some topics lack deep coverage
Building Agentic AI Systems
Strengths
+ First-mover book on a rapidly emerging topic with few good resources
+ Authors bring real production experience from Amazon and AWS
+ Covers practical patterns (CWD, reflection) that map to LangGraph and similar frameworks
+ Strong on safety and ethics, often overlooked in agent literature
Caveats
− Some readers report repetitive and over-explanatory writing
− Code examples are uneven, some feel rushed
− Field moves so fast that some specific framework references already need updating
The verdict
AI Engineering is the stronger pick overall, but Building Agentic AI Systems may suit you better if you're a AI engineers building agent systems.
AI Engineering
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Building Agentic AI Systems
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Frequently asked
Which is better, AI Engineering or Building Agentic AI Systems?
AI Engineering is the stronger pick overall, but Building Agentic AI Systems may suit you better if you're a AI engineers building agent systems.
Is AI Engineering good for beginners?
You need some software engineering experience. It's not a learn-to-code book. But you don't need a PhD in ML either. If you can write Python and understand APIs, you'll follow along.
Do I need to know LangChain or LlamaIndex first?
Familiarity helps. The patterns transfer to LangGraph, AutoGen, and Bedrock Agents, but the book assumes you know what an LLM call and a tool definition look like.