کتاب فراتر از کدنویسی حسی

مقدمه: کدنویسی حسی چیست؟

The AI Coding Spectrum: From Vibe Coding to AI-Assisted Engineering • The Vibe-Coding Approach: Code by Conversation • The AI-Assisted Engineering Approach: Structure with an AI Partner • Different Mindsets, Different Expectations • Finding Your Place on the Spectrum • Beyond Lines of Code: Programming with Intent • The Rise of the Prompt: From Instructions to Descriptions • How It Works: The Iterative Cycle and AI’s Role in Code Generation • Productivity, Accessibility, and the Changing Nature of Programming • A Glimpse of the Tools: The Emerging Ecosystem • VSCode + Copilot: Microsoft’s Integrated AI Development Platform • VSCode + Cline: The Open Source Autonomous Coding Agent • Cursor: The AI-Driven Code Editor • Windsurf: An AI-Powered IDE with Full Codebase Indexing • AI Models: The Landscape for Code Generation • Understanding Model Categories • Choosing the Right Model for Your Task • Practical Tips for Any Model • Major Models • Google Gemini: The Multimodal Coding Powerhouse • Claude: The Reasoning Virtuoso • ChatGPT: The Versatile Coding Companion • Choosing the Right Model for Your Needs • The Benefits and Limitations of Vibe Coding: A Nuanced View • Ideal Use Cases for Vibe Coding • Where AI Still Struggles • Summary and Next Steps

هنر پرامپت: ارتباط موثر با هوش مصنوعی

Prompt Engineering Fundamentals • Specificity and Clarity: Writing Prompts That Deliver • Iterative Refinement: The Feedback Loop with the AI • Comparing Two Prompts • Poor prompt • Improved prompt • Prompting Techniques: A Toolbox for Effective Communication • Zero-Shot Prompting • One-Shot and Few-Shot Prompting • Chain-of-Thought Prompting • Role Prompting • Contextual Prompting • Metaprompting • Self-Consistency (Multiple Outputs and Majority Voting) • ReAct (Reason + Act) Prompting • Advanced Prompting: Combining Techniques and Handling Complexity • Know the Model’s Limits • Stateful Conversation Versus One-Shot Prompting • Common Prompt Antipatterns and How to Avoid Them • Summary and Next Steps

مسئله ۷۰ درصد: جریان‌های کاری هوش مصنوعی که واقعاً کار می‌کنند

How Developers Are Actually Using AI • Common Failure Patterns • What Actually Works: Practical Workflow Patterns • The Golden Rules of Vibe Coding • 0. Summary and Next Steps

فراتر از ۷۰ درصد: به حداکثر رساندن مشارکت انسانی

Senior Engineers and Developers: Leverage Your Experience with AI • Be the Architect and the Editor in Chief • Use AI as a Force Multiplier for Big Initiatives • Mentor and Set Standards • Continue to Cultivate Domain Mastery and Foresight • Hone Your Soft Skills and Leadership • Midlevel Engineers: Adapt and Specialize • Learn to Manage Systems Integration and Boundaries • Build Your Domain Expertise • Master Performance Optimization and DevOps • Focus on Code Review and Quality Assurance • Learn Systems Thinking • Be Adaptable—and Never Stop Learning • Get Good at Cross-Functional Communication • Learn System Design and Architecture • Use AI! • Venture into UI and UX Design • Junior Developers: Thrive Alongside AI • Learn the Fundamentals—Don’t Skip the “Why” • Practice Problem Solving and Debugging Without the AI Safety Net • Focus on Testing and Verification • Build an Eye for Maintainability • Develop Your Prompting and Tooling Skills (Wisely) • Seek Feedback and Mentorship • Communicate and Collaborate • Shift Your Mindset: From Consuming to Creating • Summary and Next Steps

درک کد تولید شده: بازبینی، اصلاح، مالکیت

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

نمونه‌سازی مبتنی بر هوش مصنوعی: ابزارها و تکنیک‌ها

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

ساخت برنامه‌های وب با هوش مصنوعی

Setting Up the Project: Scaffolding with AI • Frontend Development Patterns with AI • Backend/API Development Patterns with AI • Database Design and Integration • Using an ORM • Database Queries • Checking AI-Generated Queries • Full Stack Integration: Marrying Frontend and Backend • Aligning Frontend and Backend Contracts • Real-Time Collaboration with AI • Testing and Validation for AI-Generated Web Applications • Examples of Successful AI-Built Web Projects • Summary and Next Steps

امنیت، نگهداری و قابلیت اطمینان

Common Security Vulnerabilities in AI-Generated Code • Improper Authentication and Authorization • Package Management Issues • Security Audits • Leverage Automated Security Scanners • Use a Separate AI as a Reviewer • Perform a Human Code Review with a Security Checklist • Penetration Testing and Fuzzing • Add Security-Focused Unit Tests • Provide Updates to Compensate for Training Cutoffs • Optimize Your Logging Practices • Use Updated Models or Tools with a Security Focus • Pay Attention to Warnings in Context • Slow Down • Building Effective Testing Frameworks for AI-Generated Systems • Performance Optimization • Ensuring Maintainability in AI-Accelerated Codebases • While Prompting • Working with Code Output • Follow-Up • Code Review Strategies • Best Practices for Reliable Deployment • Before and During Deployment • Ongoing Best Practices • Summary and Next Steps

پیامدهای اخلاقی کدنویسی حسی

Intellectual Property Considerations • What to Do If You Get Suspicious Output • Gray Areas • Transparency and Attribution • Bias and Fairness • Golden Rules for Responsible AI Use • Summary and Next Steps

عوامل کدنویسی خودمختار در پس‌زمینه

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 • Differentiate Models by Task Type • Use an Orchestration System • Human-AI Hybrid Teams • Major Players in Autonomous Coding Agents • Challenges and Limitations • Best Practices for Using AI Coding Agents Effectively • Strategically Select the Tasks Autonomous Agents Are Going to Implement • Leverage Agent-Specific Planning and Oversight Features • Manage Concurrent Agent Operations • Evolve Your Team Practices to Integrate Agents • Build Feedback Loops with Autonomous Systems • Summary and Next Steps

فراتر از تولید کد: آینده توسعه با هوش مصنوعی

AI in Testing, Debugging, and Maintenance • Automated Test Generation • Intelligent Debugging • Predictive Maintenance and Refactoring • AI-Driven Design and User Experience Personalization • Generative Design Tools • AI for UX Research • Personalized User Experiences • 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