Эдди Османи | Addy Osmani | Vibe Coding. Программирование с помощью искусственного интеллекта | Beyond Vibe Coding: From Coder to AI-Era Developer [2 книги] (2025, 2026) [PDF] [RU, EN]

Основные темы руководства:

- Постановка задач через «намерение»: как формулировать промпты, чтобы ИИ писал нужный код с первого раза.
- Преодоление «проблемы 70%»: почему генеративный ИИ быстро создает черновик, но требует контроля человека на финальных этапах.
- Три рабочих паттерна: используйте ИИ как автора черновика, напарника или автоматического валидатора кода.
- Интеграция в реальные проекты: настройка CI/CD для кода от ИИ, code review и управление техническим долгом.
- Безопасность и этика: защита от некорректного кода, вопросы авторских прав (copyleft) и предотвращение «галлюцинаций» моделей.
- Автономные агенты: как делегировать рутинные задачи фоновым ИИ-помощникам (Jules, Devin) и повысить асинхронную продуктивность.

Краткое содержание

Предисловие
Часть I. Основы
Часть II. Практика работы с ИИ
Часть III. Доверие и автономия
Об авторе
Оформление книги
Алфавитный указатель

В оригинале

Beyond Vibe Coding: From Coder to AI-Era Developer by Addy Osmani

AI is transforming software development, shifting programmers from writing code to collaborating with AI in an intent-driven workflow. Vibe coding—a prompt-first, exploratory approach where you describe what you want in natural language and let a large language model fill in the blanks—represents a radical shift in the developer's role from writing code todirecting it. However, vibe coding comes with a serious caveat: Like a high-speed exploratory vehicle, it can take you off the beaten path quickly. Beyond Vibe Coding: From Coder to AI-Era Developer explores how AI-powered coding assistants like GitHub Copilot and OpenAI Codex are reshaping the way we build software, from automating routine coding tasks to influencing architecture and design decisions.
Written by Addy Osmani, this guide provides developers, tech leads, and organizations with practical strategies to integrate AI into their workflows effectively. Learn how to formulate clear goals and constraints for the AI, review AI-generated code critically, and integrate those pieces into a coherent whole. Whether you're adopting AI tools today or preparing for the future of software engineering, this book offers insights and hands-on examples to keep your skills sharp in this evolving landscape.
- Understand how AI-assisted development is reshaping programming
- Master techniques for refining, validating, and debugging AI-generated code, and understand how and why LLM generations can go wrong
- Explore multiagent coding systems and AI-driven software workflows
- Future-proof your career by adapting to AI's growing role in development

Table of Contents
Preface

Part I. Foundations
1. Introduction: What Is Vibe Coding?
The AI Coding Spectrum: From Vibe Coding to AI-Assisted Engineering
Beyond Lines of Code: Programming with Intent
Productivity, Accessibility, and the Changing Nature of Programming
A Glimpse of the Tools: The Emerging Ecosystem
AI Models: The Landscape for Code Generation
Major Models
Choosing the Right Model for Your Needs
The Benefits and Limitations of Vibe Coding: A Nuanced View
Summary and Next Steps
2. The Art of the Prompt: Communicating Emectively with AI
Prompt Engineering Fundamentals
Specificity and Clarity: Writing Prompts That Deliver
Iterative Refinement: The Feedback Loop with the AI
Comparing Two Prompts
Prompting Techniques: A Toolbox for Effective Communication
Advanced Prompting: Combining Techniques and Handling Complexity
Summary and Next Steps

Part II. AI Coding in Practice
3. The 70% Problem: AI-Assisted WorkFows That Actually Work
How Developers Are Actually Using AI
The Golden Rules of Vibe Coding c. Summary and Next Steps
4. Beyond the 70%: Maximizing Human Contribution
Senior Engineers and Developers: Leverage Your Experience with AI
Midlevel Engineers: Adapt and Specialize
Junior Developers: Thrive Alongside AI
Summary and Next Steps
5. Understanding Generated Code: Review, Reǁne, Own
From Intent to Implementation: Understanding the AI’s Interpretation
The “Majority” Problem: Most Common Doesn’t Mean Most Appropriate
Code Readability and Structure: Patterns and Potential Issues
Debugging Strategies: Finding and Fixing Errors
Refactoring for Maintainability: Making AI Code Your Code
The Importance of Testing: Unit, Integration, and End to End
Summary and Next Steps
6. AI-Driven Prototyping: Tools and Techniques
Rapid Prototyping with AI Assistants
AI Prototyping Tools
From Concept to Prototype: Iterative Refinement
Evolving a Prototype Toward Production
Addressing Challenges in AI Prototyping
Summary and Next Steps
7. Building Web Applications with AI
Setting Up the Project: Scaffolding with AI
Database Design and Integration
Full Stack Integration: Marrying Frontend and Backend
Testing and Validation for AI-Generated Web Applications
Examples of Successful AI-Built Web Projects
Summary and Next Steps

Part III. Trust and Autonomy
8. Security, Maintainability, and Reliability
Common Security Vulnerabilities in AI-Generated Code
Security Audits
Building Effective Testing Frameworks for AI-Generated Systems
Performance Optimization
Ensuring Maintainability in AI-Accelerated Codebases
Code Review Strategies
Best Practices for Reliable Deployment
Summary and Next Steps
9. The Ethical Implications of Vibe Coding
Intellectual Property Considerations
Transparency and Attribution
Bias and Fairness
Golden Rules for Responsible AI Use
Summary and Next Steps
10. Autonomous Background Coding Agents
From Copilots to Autonomous Agents: What Are Background Coding Agents?
How Do Autonomous Coding Agents Work?
How Do Background Agents Compare to In-IDE AI Assistants?
Combining Multiple AI Models to Maximize Strengths
Major Players in Autonomous Coding Agents
Challenges and Limitations
Best Practices for Using AI Coding Agents Effectively
Summary and Next Steps
11. Beyond Code Generation: The Future of AI-Augmented Development.
AI in Testing, Debugging, and Maintenance
AI-Driven Design and User Experience Personalization
The Evolution of Project Management with AI
How Autonomous Agents Could Change Software Engineering
The Future of Programming Languages: Natural-Language-Driven Development?
How Vibe Coding Is Reshaping the Industry
Summary and Next Steps
Index.