Source
Telegram: book_cube
A post with a review of the book and key points on the preparation format.
AI Engineering Interviews
Authors: Mina Ghashami, Ali Torkamani
Publisher: O'Reilly Media, Inc. (Early Release)
Length: In progress (expected completion in December 2026)
Early Release book from O'Reilly about preparing for the GenAI interview: 300 questions with an analysis of good answers, mistakes and key points.
OriginalStatus of the book and what is available now
The book is in mode Early Release. According to O'Reilly, the benchmark for the availability of the full version is December 2026 (estimated release date: December 25, 2026).
Chapters are already available on the platform:
- Prompt Engineering
- Machine Learning Foundations
- Transformer Architecture
Related chapter
Prompt Engineering for LLMs
Prompting practices and LLM workflows as a basis for the interview block.
What does the book format promise?
300 real industry questions on GenAI/AI Engineering.
For each question: expected answer shape, key points and common mistakes.
Covering the complete interview process, from basic knowledge to advanced roles.
Focus on practical explanation of architecture, learning, inference and evaluation.
How is this perceived in practice?
The spirit of the book is reminiscent exam preparation guide: There is a basic theory, then a large pool of typical questions and expected answers. It works well as a tool for self-testing and quick pre-interview preparation, but is less suitable as a single fundamental textbook.
Strengths
High application value for interview preparation in a short time.
A clear structure of questions and quick feedback on the quality of the answer.
Explanations of complex topics in simple language, with visual support.
Suitable as a checklist for self-testing before an interview.
Limitations and how to level them
The Q&A format is useful for training, but does not replace fundamental textbooks.
There is a risk of learning patterns without a deep understanding of the principles.
The book is in Early Release status, so the content will still change.
Related chapter
AI Engineering (Chip Huyen)
A more systematic look at the development of AI products in production.
Practical reading plan
- First close the base: Prompting, ML foundations, Transformer fundamentals.
- Then go through the questions in blocks by topic, fixing weak areas.
- For each topic, prepare 2-3 detailed oral answers with examples.
- 1-2 weeks before the interview, do mock sessions using mixed question sets.
Who is the book especially useful for?
- Engineers who take on the roles of GenAI Engineer / AI Engineer.
- Developers who need a structured interview drill on LLM topics.
- Candidates who want to quickly close gaps before a series of interviews.
Where to read and what to discover nearby
O'Reilly: AI Engineering Interviews
Early Release version of the book and updates as it is written.
Telegram review
Brief abstracts and personal assessment of the book format.
For a more fundamental basis, see also Hands-On LLM And ML System Design.