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Overview

The SDD workflow transforms vague ideas into working systems through a structured, iterative process. Each step builds upon the previous one, creating a tight feedback loop between intent, specification, and implementation.
Unlike traditional development where specs are written once and forgotten, SDD treats specifications as living artifacts that continuously evolve alongside your understanding of the problem.

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The Complete Workflow

1

Establish Project Principles

Create your project’s governing principles using /speckit.constitution. These immutable principles guide all subsequent development decisions.
/speckit.constitution Create principles focused on code quality, 
testing standards, user experience consistency, and performance requirements
This creates .specify/memory/constitution.md with your architectural DNA—principles that shape how specifications become code.
2

Capture the Idea

The workflow begins with an idea—often vague and incomplete. Through iterative dialogue with AI, this idea becomes a comprehensive PRD using /speckit.specify.
Focus on the what and why, not the tech stack. Describe user needs, business goals, and acceptance criteria.
/speckit.specify Build an application that helps organize photos in 
separate albums grouped by date, with drag-and-drop reorganization
What happens:
  • AI asks clarifying questions
  • Identifies edge cases
  • Helps define precise acceptance criteria
  • Creates a feature branch (e.g., 001-photo-albums)
  • Generates specs/001-photo-albums/spec.md
What might take days of meetings in traditional development happens in hours of focused specification work.
3

Clarify Requirements (Recommended)

Before creating technical plans, use /speckit.clarify to address underspecified areas through structured questioning.
/speckit.clarify
This structured workflow:
  • Asks sequential, coverage-based questions
  • Records answers in a Clarifications section
  • Reduces rework downstream
  • Ensures all stakeholders have shared understanding
Run this before /speckit.plan to avoid rebuilding technical plans when requirements change.
4

Research and Context Gathering

Throughout the specification process, research agents gather critical context:
  • Library compatibility investigations
  • Performance benchmarks
  • Security implications
  • Organizational constraints (database standards, auth requirements, deployment policies)
This research happens automatically during /speckit.plan and is documented in research.md.
5

Generate Implementation Plan

Use /speckit.plan to translate business requirements into technical architecture.
/speckit.plan Use Vite with minimal libraries. Vanilla HTML, CSS, 
and JavaScript. Images stored locally, metadata in SQLite database.
AI generates:
  • plan.md - Technical architecture and implementation phases
  • research.md - Technology choices with documented rationale
  • data-model.md - Entity definitions and relationships
  • contracts/ - API specifications and interfaces
  • quickstart.md - Key validation scenarios
Every technology choice has documented rationale. Every architectural decision traces back to specific requirements.
6

Validate Consistency

Use /speckit.analyze to cross-check artifacts for consistency, coverage, and alignment.
/speckit.analyze
AI analyzes specifications for:
  • Ambiguity and contradictions
  • Gaps in requirements coverage
  • Misalignment between spec and plan
  • Missing acceptance criteria
This isn’t a one-time gate—it’s an ongoing refinement that continuously improves quality.
7

Break Down Into Tasks

Use /speckit.tasks to create an actionable task list from your implementation plan.
/speckit.tasks
Generates tasks.md with:
  • Tasks organized by user story
  • Dependency management (models → services → endpoints)
  • Parallel execution markers [P]
  • Exact file paths for implementation
  • Test-driven development structure
  • Checkpoint validation for each phase
8

Execute Implementation

Use /speckit.implement to execute all tasks and build your feature.
/speckit.implement
Code generation begins with the implementation plan as the guide:
  • Domain concepts become data models
  • User stories become API endpoints
  • Acceptance scenarios become tests
  • Tasks execute in correct order respecting dependencies
Implementation and testing merge through specification—test scenarios aren’t written after code, they’re part of the specification that generates both.
9

Continuous Feedback Loop

The feedback loop extends beyond initial development:
  • Production metrics inform specification refinement
  • Incidents trigger spec updates for next regeneration
  • Performance bottlenecks become non-functional requirements
  • Security vulnerabilities become constraints affecting all future generations
This iterative dance between specification, implementation, and operational reality is where true understanding emerges.

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Workflow Characteristics

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Team Process

SDD supports collaborative development:

Version Control

Team-reviewed specifications are expressed and versioned, created in branches, and merged like code.

Living Documentation

When a product manager updates acceptance criteria, implementation plans automatically flag affected technical decisions.

Continuous Evolution

When an architect discovers a better pattern, the PRD updates to reflect new possibilities.

Shared Understanding

Specifications become the common language between product, design, and engineering.

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Early Generation

Code generation begins as soon as specifications and implementation plans are stable enough, but they do not have to be complete.
Early generations might be exploratory—testing whether the specification makes sense in practice. This validates assumptions before investing in complete specifications.Benefits:
  • Discover specification gaps through concrete implementation
  • Validate technical feasibility early
  • Get working prototypes for stakeholder feedback
  • Identify missing edge cases in actual usage

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SDLC Transformation

SDD transforms the traditional Software Development Lifecycle:
Traditional SDLCSpec-Driven Development
Requirements → discrete phaseRequirements → continuous activity
Design → separate from codingDesign → generates implementation
Testing → after implementationTesting → part of specification
Maintenance → manual updatesMaintenance → specification evolution
Change → disruptiveChange → systematic regeneration
Requirements and design become continuous activities rather than discrete phases that happen once and are forgotten.

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Time Comparison

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Traditional Approach

1. Write PRD (2-3 hours)
2. Create design documents (2-3 hours)
3. Set up project structure (30 minutes)
4. Write technical specifications (3-4 hours)
5. Create test plans (2 hours)
Total: ~12 hours of documentation work

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SDD Approach

# 5 minutes - Create specification
/speckit.specify [describe feature]

# 5 minutes - Generate implementation plan  
/speckit.plan [tech stack choices]

# 5 minutes - Generate task breakdown
/speckit.tasks

Total: ~15 minutes to comprehensive documentation
In 15 minutes, you have:
  • Complete feature specification with user stories
  • Detailed implementation plan with technology choices
  • API contracts and data models
  • Comprehensive test scenarios
  • All documents versioned in a feature branch

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Optional Quality Commands

Enhance your workflow with additional validation:

/speckit.analyze

Cross-artifact consistency and coverage analysis. Run after /speckit.tasks, before /speckit.implement.

/speckit.checklist

Generate custom quality checklists that validate requirements completeness, clarity, and consistency—like “unit tests for English.”

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Next Steps

Understand the Philosophy

Explore the core principles and design decisions behind SDD

Get Started

Begin practicing Spec-Driven Development in your projects

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