Building Production-Grade Software with AI-Assisted Development
Introduction: The Vibe Engineering Revolution
- What Is Vibe Engineering
- The Karpathy Moment and Why It Matters
- Vibe Coding vs. Agentic Engineering
- What This Book Will Teach You
Chapter 1: The AI-Assisted Development Landscape
- From Autocomplete to Agentic Coding
- The Tool Landscape: IDEs, CLIs, and Platforms
- What the Data Says About Productivity
- The Code Quality Debate
Chapter 2: Your AI Development Toolkit
- IDE-Native Assistants: Cursor and Windsurf
- Terminal Agents: Claude Code and OpenAI Codex CLI
- Inline Autocomplete: GitHub Copilot and Alternatives
- Browser-Based Platforms: Replit, Bolt, and Lovable
- Building Your Tool Stack
Chapter 3: Context Engineering
- Why Context Is Your Most Valuable Resource
- The Anatomy of a Great CLAUDE.md
- Token Budgets and Attention Decay
- Just-in-Time Retrieval and Progressive Disclosure
- Structured Note-Taking and External Memory
Chapter 4: Prompt Strategies for Code Generation
- The Spec-First Prompt Pattern
- Chain-of-Thought for Architectural Decisions
- Few-Shot Examples and Negative Constraints
- Iterative Refinement Loops
- Model Selection by Task Type
Chapter 5: Spec-Driven Development
- From Vibe Coding to Specs
- Writing Effective Specifications
API Endpoints
Non-Functional Requirements
Out of Scope (for this iteration)
- The Plan-Build-Verify Cycle
- Tools That Support Spec-Driven Workflows
Chapter 6: Architecture and Design for AI-Assisted Development
- Designing for AI Generation
- Modular Monoliths and Bounded Contexts
- API-First Architecture
- Event-Driven Patterns and Async Workflows
- Anti-Patterns to Avoid
Chapter 7: Testing AI-Generated Code
- Why AI-Generated Code Needs Different Testing
- Test Generation with AI Assistants
- Catching Tautological Tests
- Fuzz Testing and Property-Based Testing
- Integration and End-to-End Coverage
- Troubleshooting: Common AI Testing Pitfalls
- The Testing Checklist for AI Code
Chapter 8: Debugging Strategies
- The Five-Step Debugging Methodology
- Common Failure Patterns in AI-Generated Code
- Production Debugging with AI Agents
- Observability and Distributed Tracing
- When to Fall Back to Classical Debugging
Chapter 9: Security and Supply Chain
- The Hallucination Attack Surface
- Slopsquatting and Supply Chain Risks
- Case Study: Slopsquatting Incident Post-Mortem
- Injection Vulnerabilities in AI Code
- Secrets Management and Credential Safety
- Security Scanning in the AI Pipeline
Chapter 10: CI/CD Integration
- The AI-Native CI/CD Pipeline
- Automated Code Review with AI
- AI-Augmented Test Generation in CI
- Self-Healing Pipelines
- Deployment Strategies for AI-Assisted Teams
- Knowledge Sharing and Context Propagation
- Onboarding and Team Standards
- Measuring What Matters: DORA Metrics and Beyond
Chapter 12: The Model Context Protocol (MCP)
- What Is MCP and Why It Matters
- The Client-Server Architecture
- Building Custom MCP Servers
- Security and Authorization in MCP
- The Growing Ecosystem
Chapter 13: Multi-Agent Orchestration
- From Single Agent to Multi-Agent Systems
- Orchestration Patterns: Planner, Supervisor, Hive Mind
- Frameworks: LangGraph, CrewAI, Microsoft Agent Framework
- Parallel Execution and Worktree Strategies
- Governance and Guardrails
Chapter 14: Real-World Project Walkthrough
- Project Brief: A Task Management API
- Phase 1: Specification and Planning
- Phase 2: Scaffold and Architecture
- Phase 3: Implementation with Agents
- Phase 4: Testing and Validation
- Phase 5: Deployment and Monitoring
Chapter 15: AI-Assisted Development Across Domains
- Mobile Development with AI Assistants
- Data Engineering Pipelines with AI
- Frontend Framework Integration
- Infrastructure as Code and DevOps with AI
- Cross-Domain AI Workflow Patterns
Chapter 16: Maintenance, Migration, and Evolution
- Refactoring AI-Generated Code
- Legacy System Migration
- Performance Optimization
- Managing Technical Debt at Scale
- Keeping Your Codebase AI-Friendly
Conclusion: The Future of Vibe Engineering
- The Skills That Will Endure
- What Comes Next
- Your Role in the AI-Native Future
