# Reader reviews

> What readers say about AI-Native Software Engineering, in their own words.

- **Source:** https://ainativesoftware.engineering/reviews
- **Site:** AI-Native Software Engineering — https://ainativesoftware.engineering/book

What engineers who read AI-Native Software Engineering say about it, in their own words. The page shows a screenshot of each post or comment; the words are copied here verbatim.

- **Reviews:** 4
- **Photos:** 1
- **Read the book:** [On O'Reilly Media](https://www.oreilly.com/library/view/ai-native-software-engineering/0642572352530/)

## Rasul Rzayev, LinkedIn

- **Role:** Solution Architect, Enterprise AI & Agentic Systems
- **Posted:** 2026-10-31

> I recently had the chance to read your O'Reilly book and honestly it's one of the best books I've read in recent months. I really appreciated the topics, clear explanations and level of details. Thank you for writing such a great book!

## Zilal Eiz Al Din, LinkedIn

- **Role:** AI Software Engineer at Keiji AI
- **Posted:** 2026-09-25
- **Original:** https://www.linkedin.com/feed/update/urn:li:activity:7439385839492685824/?dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287509131854902349824%2Curn%3Ali%3Aactivity%3A7439385839492685824%29

> I really liked your book! I bought other books and your book is still the best overall. Your answer to this question 'What do I need to be good at to stay valuable as AI gets better?' is really beneficial to me.

## Sergio Lissanou, LinkedIn

- **Role:** Full-Stack Developer (JavaScript, React, Node.js), CEO of SCRIPTY
- **Posted:** 2026-09-01
- **Original:** https://www.linkedin.com/posts/sergiolissanou_ai-softwareengineering-aiagents-share-7500464447245717504-3vA5/

> I used to think the future of software development was about getting better at prompting AI. I now think I was wrong.
> I just finished reading AI-Native Software Engineering by Alfonso Graziano published by O'Reilly, and it fundamentally changed the way I think about AI-assisted software development.
>
> AI isn't just changing how we write code. It's changing how we need to think about software development itself.
> Before, I tended to see AI assistants as tools that could generate code from a prompt.
> After this book, I see them much more as agents that need the right environment, context, clear objectives, and guardrails to produce reliable results.
>
> Here are the main ideas I'm taking away:
> 1. Context matters just as much as the prompt
> A good prompt isn't enough.
> An agent needs to understand the project, its rules, constraints, architecture, previous decisions, and the relevant files.
>
> 2. Code explains the "what", specifications explain the "why"
> An agent can read my code and understand what it does.
> But it can't always understand why certain decisions were made.
> That's where specifications and ADRs become essential.
> They become, in a way, the system's memory, preserving the intent, constraints, and reasoning behind technical decisions.
>
> 3. We need to stop asking AI to act too quickly
> One habit I particularly want to adopt.
> Before asking an agent to code, ask it to PLAN.
> It's an interesting shift from vibe coding toward a much more structured approach to software development.
>
> 4. Specifications aren't documentation you write afterward
> I used to think of specifications as something you write once you fully understand the problem.
> This book presents a different perspective:
> A specification is itself a thinking tool.
> Writing down what you want to build forces you to clarify the objective, constraints, success criteria, and what is out of scope.
>
> Ultimately, I no longer want to simply learn how to prompt AI better.
> I want to learn how to design an environment in which AI can work effectively.
> A book I would highly recommend to anyone experimenting with AI agents, AI-assisted coding, and vibe coding today.

## Anton Vishnyakov, LinkedIn

- **Role:** Platform Engineering, Golden Kubestronaut
- **Posted:** 2026-08-26
- **Original:** https://www.linkedin.com/posts/antonvishnyakov_ai-native-software-engineering-book-by-alfonso-share-7498183727982882816-faxT/

> Been reading early preview of AI-Native Software Engineering book by Alfonso Graziano, and so far, I would consider it as a must-have read for anyone looking to move from ad-hoc prompting to well-structured, spec-driven development workflows. It might be a good onboarding read too.
>
> The book offers useful mental models and approaches which remain relevant regardless of the changing AI tooling landscape. I like the organic flow of chapters - core principle and mindset, moving from LLMs to agents, thinking about prompting and context engineering, eventually moving into spec-driven development. Moreover, it's packed with links to research papers and useful blog posts, providing more context for a deeper dive.
>
> Looking forward to finish remaining chapters on SDD frameworks, verification and quality gates, agent orchestration and scaling AI-native teams.
>
> Thank for putting all this together, Alfonso Graziano, it's been a great read!

## Where the book has turned up

- [At the O'Reilly booth](https://ainativesoftware.engineering/images/reviews/photos/oreilly-booth-agentcon.jpg), AgentCon + MCPCon North America. Four people at the O'Reilly booth smiling and pointing at a large screen that shows the AI-Native Software Engineering page on the O'Reilly learning platform.

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_AI-Native Software Engineering by Alfonso Graziano (O'Reilly Media, Early Release; print edition February 2027). Every page of ainativesoftware.engineering is also served as Markdown: append `.md` to any URL. Index: https://ainativesoftware.engineering/llms.txt — whole site in one file: https://ainativesoftware.engineering/llms-full.txt._