Designing Machine Learning Systems versus LLM Engineer's Handbook.
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
Paul Iusztin, Maxime Labonne
Pages
368
522
Published
2022
2024
Publisher
O'Reilly Media
Packt Publishing
Level
intermediate
intermediate to advanced
Amazon Rating
4.6/5 (933)
4.5/5 (184)
Goodreads Rating
4.44/5 (1,102)
3.9/5 (62)
Designing Machine Learning Systems
Strengths
+ Covers the entire ML lifecycle from data to monitoring
+ Focuses on principles that outlast specific tools
+ Clear and accessible writing for complex topics
+ Production-focused, not just academic theory
Caveats
− High-level overview may feel shallow for experienced ML engineers
− Limited LLM coverage (published pre-ChatGPT in 2022)
− Not enough specific code examples or tool recommendations
LLM Engineer's Handbook
Strengths
+ End-to-end production focus covering the full LLM pipeline
+ Bridges the gap between research papers and real-world implementation
+ Authors bring real experience from building GenAI systems at scale
+ Amazon Bestseller with 10,000+ copies sold globally
Caveats
− Writing tends to over-explain trivial details while skipping architectural decisions
− Code examples have inconsistent patterns and small bugs
− Breadth-first approach means limited depth on any single topic
The verdict
Read Designing Machine Learning Systems first to build foundations, then move to LLM Engineer's Handbook for advanced concepts.
Designing Machine Learning Systems
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LLM Engineer's Handbook
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Frequently asked
Which is better, Designing Machine Learning Systems or LLM Engineer's Handbook?
Read Designing Machine Learning Systems first to build foundations, then move to LLM Engineer's Handbook for advanced concepts.
Is Designing Machine Learning Systems still relevant in 2026?
The core principles of data management, evaluation, and monitoring apply to any ML system, including LLMs. But for LLM-specific topics, pair it with the author's newer book, AI Engineering.
Is the LLM Engineer's Handbook good for beginners?
You need familiarity with Python, basic ML concepts, and ideally some cloud/AWS experience. It's not a first book on AI, but it's approachable for mid-level engineers.