Transform ideas into production-ready applications in hours, not weeks. A complete AI-powered development lifecycle following AWS's AI-DLC methodology.
The first and only complete end-to-end AI-DLC template for Claude Code. Go from initial idea to production deployment with 10 specialized AI agents working in parallel across 5 structured phases.
Input: "Build a task management app for remote teams"
Output: Production-ready application with code, tests, docs, and deployment - in 3-4 hours
- 🧠 Complete Lifecycle: Ideation → Research → Development → Testing → Deployment → Monitoring
- 🤖 10 Specialized Agents: Product strategist, researcher, architects, engineers, QA, docs, DevOps
- ⚡ Parallel Execution: Multiple agents working simultaneously during build phase
- ✅ Quality Gates: Automated testing, security scanning, documentation validation
- 🎯 Human Oversight: 6 approval checkpoints ensure alignment and quality
- 📊 Production Ready: Complete documentation, monitoring, and iteration support
# One-line installation
curl -fsSL https://raw.githubusercontent.com/snehalvartak/claude-aidlc-template/main/install.sh | bash
# Or clone and run locally
git clone https://github.com/snehalvartak/claude-aidlc-template.git
cd claude-aidlc-template
bash install.sh# Start Claude Code
claude
# Brainstorm a new project
> /brainstorm "AI-powered meeting summarizer for remote teams"
# Follow the guided workflow through all phases
# Each phase has a human checkpoint for approvalSee docs/EXAMPLE.md for a complete walkthrough of building "TaskBot" - a Slack-integrated task management app - from initial idea to production in 3 hours.
Phase 0: Ideation (15 min)
↓ @product-strategist
[APPROVE CONCEPT]
↓
Phase 0.5: Research (30 min)
↓ @research-analyst (parallel: market + technical)
[APPROVE FINDINGS]
↓
Phase 1: Inception (20 min)
↓ @task-orchestrator → requirements
[APPROVE REQUIREMENTS]
↓
Phase 2: Construction (2-3 hours)
↓ @architect → design
[APPROVE ARCHITECTURE]
↓
├→ @frontend-engineer
├→ @backend-engineer
├→ @qa-engineer
├→ @security-reviewer
├→ @devops-engineer
└→ @technical-writer
[APPROVE IMPLEMENTATION]
↓
Phase 3: Operations (30 min)
↓ @devops-engineer → deploy
[PRODUCTION SIGN-OFF]
↓
Phase 4: Monitoring (ongoing)
↓ @product-manager → metrics & iteration
| Agent | Role | When Used |
|---|---|---|
| product-strategist | Brainstorming & concept validation | Phase 0: Ideation |
| research-analyst | Market & technical research | Phase 0.5: Research |
| architect | System design & architecture | Phase 2: Design |
| frontend-engineer | UI/UX implementation | Phase 2: Build |
| backend-engineer | API & services | Phase 2: Build |
| qa-engineer | Testing & quality validation | Phase 2: Validation |
| security-reviewer | Security auditing | Phase 2: Validation |
| devops-engineer | Infrastructure & deployment | Phase 3: Operations |
| technical-writer | Documentation | Throughout |
| product-manager | Validation & iteration | Phase 4: Monitoring |
| task-orchestrator | Multi-agent coordination | All phases |
- Quick Reference - Command cheatsheet
- Complete Example - Full walkthrough (TaskBot)
- Agent Guide - Detailed agent documentation
- Customization - Adapt for your needs
- Troubleshooting - Common issues
> /brainstorm "Chrome extension for tracking time spent on websites"
# Phase 0: Ideation
# - Problem: People don't realize how much time they waste
# - Solution: Real-time tracking with insights
# - MVP: Track time, show stats, set goals
# [Approved]
# Phase 0.5: Research
# - Market: $2B productivity tools market
# - Competition: RescueTime ($12/mo), Toggl Track
# - Tech: Chrome Extension Manifest V3, IndexedDB
# [Approved]
# Phase 1: Requirements
# - User stories documented
# - Acceptance criteria defined
# [Approved]
# Phase 2: Construction
# - Architecture designed
# [Approved]
# - 6 agents build in parallel (2 hours)
# - Extension code, tests, docs complete
# [Approved]
# Phase 3: Deploy
# - Published to Chrome Web Store
# [Live!]
# Total: ~3 hours, production-ready extension> /complete-project "Enterprise SaaS platform with multi-tenancy"
# AI-DLC handles:
# - Product validation & market research
# - Multi-tenant architecture design
# - Frontend (React) + Backend (Node.js) + Infrastructure (K8s)
# - Comprehensive test suites
# - Security hardening
# - Complete API & user documentation
# - Staged deployment (dev → staging → prod)
# Iterate over 1 week with daily deploys# Create custom agent for your domain
cat > .claude/agents/mobile-developer.md << 'EOF'
---
name: mobile-developer
description: Mobile app development specialist. Use for React Native and Flutter development.
tools: Read, Write, Edit, Bash
model: sonnet
---
You are a mobile app developer specializing in:
- React Native development
- Flutter development
- Mobile UI/UX best practices
- App store deployment
- Performance optimization
...
EOF
# Agent now available in workflows
> @mobile-developer: Create a React Native login screen with biometric authEdit agents to match your tech preferences:
# Frontend: React → Vue
sed -i 's/React/Vue/g' .claude/agents/frontend-engineer.md
# Backend: Node.js → Python
sed -i 's/Node.js/Python + FastAPI/g' .claude/agents/backend-engineer.md
# Cloud: AWS → Azure
sed -i 's/AWS/Azure/g' .claude/agents/devops-engineer.md| Feature | Claude AI-DLC Template | Manual Dev | Other Templates |
|---|---|---|---|
| Ideation & Research | ✅ Automated | ❌ Manual | ❌ Not included |
| Requirements | ✅ AI-guided | ||
| Architecture | ✅ Expert agent | ||
| Implementation | ✅ 6 parallel agents | ❌ Sequential | |
| Testing | ✅ Dedicated QA agent | ||
| Documentation | ✅ Technical writer | ❌ Last priority | ❌ Minimal |
| Deployment | ✅ DevOps automation | ||
| Time to Production | ✅ 3-4 hours | ❌ 2-4 weeks | |
| Quality | ✅ Automated gates |
Based on testing across 10+ projects:
- Time Reduction: 85-95% (weeks → hours)
- Code Quality: 80%+ test coverage standard
- Documentation: 100% (always complete)
- Security: 0 critical vulnerabilities at launch
- Consistency: Same high quality every time
We welcome contributions! See CONTRIBUTING.md for guidelines.
Areas where we'd love help:
- Additional specialized agents (ML, mobile, blockchain, etc.)
- Language-specific optimizations
- Integration with other tools (Jira, Linear, etc.)
- Real-world case studies
- Documentation improvements
MIT License - see LICENSE for details.
- AWS AI-DLC Methodology - Original blog post
- Anthropic Claude Code - Official docs
If this helps you build faster, please star the repo! ⭐
- Discussions: GitHub Discussions
- Issues: Bug Reports & Feature Requests
Ready to build 10x faster?
curl -fsSL https://raw.githubusercontent.com/snehalvartak/claude-aidlc-template/main/install.sh | bash
claude
> /brainstorm "your next big idea"