Spec-Driven Development with AI: The Blueprint

📝 The Problem with Chat

Chatting with an AI is linear and ephemeral. If you ask for a complex feature (e.g., “A shopping cart system”), the AI might forget requirements mentioned 5 messages ago.

Spec-Driven Development (SDD) changes the approach. Instead of asking for code directly, you ask the AI to help you write a Specification Document.

🏗️ The Workflow

1. Drafting: “Claude, I want to build a shopping cart. Help me list the necessary Use Cases and edge cases.”
2. Refining: Create a specs/cart_feature.md file.
   • Data Models (CartItem, Product).
   • Business Rules (“You can’t add more items than stock”).
   • UI States.
3. Approval: Review the spec. This is your contract.
4. Generation: “Claude, implement the CartRepository following specs/cart_feature.md.”

📄 Example Spec (specs/login.md)

# Login Feature Specification

## Requirements
1.  Email must be valid format.
2.  Password must be > 8 chars.
3.  After success, save token to EncryptedSharedPreferences.

## Architecture
-   `LoginUseCase`: Handles validation and repo call.
-   `LoginViewModel`: Exposes `StateFlow<LoginUiState>`.

## Edge Cases
-   Network timeout -> Show "Retry" button.
-   Invalid credentials -> Shake animation on input.

🚀 Benefits

• Consistency: The AI refers to a static source of truth.
• Documentation: You get free documentation for your project.
• Iterability: If the code is wrong, you fix the Spec and regenerate, rather than arguing with the chat.

🎯 Conclusion

Treat the AI as a Junior Developer. You wouldn’t tell a Junior “make a cart” and walk away. You would give them a spec. Do the same with LLMs.