Spec-Driven Development

Spec-Driven Development (SDD)

In an AI-driven world, the highest-leverage activity for a developer is no longer writing syntax, but defining intent.

The Paradigm Shift

Traditional SDLC	AI-Driven SDLC
Input: Jira Ticket (Vague)	Input: Technical Spec (Detailed)
Process: Manual Code Writing	Process: AI Generation + Human Review
Bottleneck: Typing Speed / Syntax Knowledge	Bottleneck: Clarity of Thought / Requirements
Artifact: Code	Artifact: Spec + Code

How It Works

SDD treats the specification as the “source of truth” and the code as a compiled artifact.

graph LR
    A[Idea] -->|Human writes| B[Spec.md]
    B -->|AI reads| C[Code Generation]
    C -->|AI/Human Check| D[Tests]
    D -->|Pass| E[Merge]
    
    B -.->|Update Spec| B

The Workflow

1. Write the Spec: Describe the feature in natural language. Include inputs, outputs, error handling, and examples.
2. Generate the Code: Use an agent (Cursor, Windsurf, Copilot Workspace) to implement the spec.
3. Generate the Tests: Ask the AI to write tests based only on the spec, then run them against the code.
4. Refine: If tests fail, update the code (or the spec if the requirement was wrong).

Why This Matters for Enterprise

• Documentation stays fresh: The spec is the documentation. You can’t change the code without updating the spec effectively.
• Reduced Ambiguity: Writing a spec forces you to think through edge cases before coding starts.
• Junior Empowerment: Junior devs can produce senior-level code if they can write a clear spec.

Example: API Spec

Instead of writing a Python function, you write:

Spec: Create a REST endpoint POST /orders that accepts a JSON order.

• Validate functionality: Check inventory.
• Business Logic: Apply discount if user.is_vip.
• Output: Returns 201 with Order ID.
• Error: Returns 400 if stock is low.

The AI handles the boilerplate, imports, and error handling structure.