Chapter 5: Spec-Driven Development with Claude Code
Spec-Driven Development (SDD) represents a paradigm shift in how software is created with AI assistance. Rather than treating AI coding agents as sophisticated autocomplete tools, SDD establishes specifications as the primary artifact of software development, with code becoming a generated output derived from these human-authored specifications.
This chapter teaches SDD using native Claude Code capabilities only—Memory (CLAUDE.md), Subagents, Tasks, and Hooks. You'll learn the complete four-phase workflow that transforms vibe coding chaos into production-ready implementations.
The Evolution from Vibe Coding
The emergence of AI coding assistants has fundamentally altered how developers approach software creation. In the early days, developers quickly adopted vibe coding—an intuitive, conversational approach where developers describe what they want and receive code in return. This method works remarkably well for quick prototypes and exploring possibilities.
However, as practitioners moved from prototyping to building production systems, the limitations of vibe coding became apparent. Each iteration loses context from previous discussions. The agent makes reasonable assumptions that turn out wrong. The resulting code may work but does not align with the project's existing patterns or architecture.
Spec-Driven Development emerged as a response to these challenges. Rather than iterative discovery through conversation, SDD provides comprehensive specifications upfront. The AI agent receives a complete picture of what to build, why it matters, and critically—what NOT to build.
Prerequisites
This chapter builds directly on:
- Chapter 3 — You learned Claude Code's core capabilities: CLAUDE.md for persistent memory (Lesson 5), Subagent orchestration (Lesson 9), and the foundational tools that enable agentic workflows
- Chapter 4 — You learned context engineering: why context quality determines agent reliability, context isolation patterns (Lesson 9), and the Tasks system for persistent state (Lesson 4)
SDD is the methodology that orchestrates these capabilities into production-ready workflows.
SDD Tools Landscape
Spec-Driven Development is a methodology, not a single tool. Several frameworks implement it:
| Tool | Approach | Notable Feature |
|---|---|---|
| Amazon Kiro | Requirements → Design → Tasks | Lightweight three-document workflow |
| GitHub Spec-Kit | Constitution → Specify → Plan → Tasks | Open-source, multi-agent compatible |
| Tessl | Spec-as-Source | Radical approach: code regenerated from specs |
| CC-SDD | Cross-tool | Works with Claude Code, Cursor, Gemini CLI |
This chapter uses native Claude Code capabilities only—Memory (CLAUDE.md), Subagents, Tasks, and Hooks. No external frameworks required. The principles transfer to any SDD tool.
📚 Teaching Aid
What You'll Learn
By the end of this chapter, you'll be able to:
- Explain why vibe coding fails for production systems
- Distinguish between the three SDD implementation levels (Spec-First, Spec-Anchored, Spec-as-Source)
- Execute the four-phase SDD workflow using native Claude Code features
- Design effective specifications that AI agents can implement reliably
- Apply parallel research patterns with subagents
- Use the Task system for dependency-aware orchestration with atomic commits
- Decide when SDD adds value vs when simpler approaches suffice
Key Prompt Patterns
| Pattern | When to Use | Example |
|---|---|---|
| Parallel Research | Starting investigation | "Spin up multiple subagents for your research task" |
| Spec-First | Force written artifact | "Your goal is to write a report/document" |
| Interview | Surface ambiguities | "Use ask_user_question tool before we implement" |
| Task Delegation | Complex implementation | "Use the task tool, each task by subagent, commit after each" |
| Role Assignment | Set expectations | "You are the main agent and your subagents are your devs" |
Remember the thesis: General Agents BUILD Custom Agents. SDD is HOW you orchestrate complex projects with Claude Code to produce production-quality systems.
References & Further Reading
This chapter synthesizes insights from:
- Osmani, A. (2025). "How to write a good spec for AI agents." addyosmani.com
- Böckeler, B. (2025). "Understanding Spec-Driven-Development: Kiro, spec-kit, and Tessl." martinfowler.com
- GitHub. (2025). "Spec-driven development with AI: Get started with a new open source toolkit." GitHub Blog
- Anthropic. (2025). "Claude Code: Best practices for agentic coding." anthropic.com/engineering
- Opalic, A. (2026). "Spec-Driven Development with Claude Code in Action." alexop.dev
For the complete academic foundation, see the Panaversity Research Paper: Spec-Driven Development with Claude Code: A Comprehensive Guide to AI-Native Software Development (February 2026).