AI Engineering versus Hands-On Large Language Models.
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 May 2026
Author
Chip Huyen
Jay Alammar, Maarten Grootendorst
Pages
532
425
Published
2025
2024
Publisher
O'Reilly Media
O'Reilly Media
Level
intermediate
beginner to intermediate
Amazon Rating
4.4/5 (899)
4.5/5 (392)
Goodreads Rating
4.4/5 (1,061)
4.29/5 (254)
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
Hands-On Large Language Models
Strengths
+ 275+ custom diagrams make abstract concepts visual and intuitive
+ Accessible to beginners without prior PyTorch/TensorFlow knowledge
+ Practical code examples covering real use cases like semantic search and RAG
+ Well-structured progression from foundations to advanced techniques
Caveats
− Limited depth on transformer internals despite the author's blog reputation
− Image generation sections lack clarity
− May be too introductory for experienced ML practitioners
The verdict
Read Hands-On Large Language Models first to build foundations, then move to AI Engineering for advanced concepts.
AI Engineering
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Hands-On Large Language Models
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Frequently asked
Which is better, AI Engineering or Hands-On Large Language Models?
Read Hands-On Large Language Models first to build foundations, then move to AI Engineering for advanced concepts.
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.
Is Hands-On Large Language Models good for beginners?
Yes, it's one of the most beginner-friendly LLM books available. No PyTorch or TensorFlow experience needed. The 275+ diagrams carry a lot of the explanation load.