Use AI-DLC Workflow to analyze and modernize an existing e-commerce codebase
A sample e-commerce application with user authentication, product catalog, shopping cart, checkout, order history, and category filtering. Use AI-DLC Workflow to analyze and modernize it — the workflow automatically reverse-engineers the codebase before you start building.
When you start the workflow in this repo, Workspace Detection finds existing code (Node.js backend, React frontend, SQLite database) and flags it as a brownfield project. The workflow then automatically runs Reverse Engineering before Requirements Analysis — it analyzes all packages and components, generates architecture documentation, code structure docs, API documentation, component inventory, interaction diagrams, technology stack docs, and dependency documentation.
All of this goes into aidlc-docs/inception/reverse-engineering/. You don't need to tell the AI about the codebase — it reads it and documents it for you. The reverse engineering output becomes the foundation for whatever you build next.
When you paste any of the intents below, AI-DLC Workflow will:
The AI will present approval gates at each stage — review and approve to continue, or request changes if needed.
These are ready-to-use intents. Pick one, paste it into your AI assistant in this repo, and the workflow takes over.
Feature Additions
Using AI-DLC, add a product review system where customers can rate products from 1-5 stars, write text reviews, see average ratings on product cards, and filter/sort products by rating. Only allow reviews from customers who purchased the product.
Using AI-DLC, add a wishlist feature where users can save products to a wishlist, view all wishlist items on a dedicated page, and move items from wishlist to cart.
Using AI-DLC, implement order tracking where customers can see real-time order status (Processing, Shipped, Delivered), view estimated delivery date, and receive notifications on status changes.
Using AI-DLC, add advanced product search with full-text search across name and description, filter by category, price range, and stock availability, sort by price, rating, or newest, and search suggestions as user types.
Using AI-DLC, create an admin dashboard to view sales analytics (daily, weekly, monthly), see top-selling products, monitor inventory levels, track user registrations, and export reports as CSV.
Technical Improvements
Using AI-DLC, optimize the application for better performance — add caching for the product catalog, implement pagination for product lists, add lazy loading for images, and optimize database queries with indexes.
Using AI-DLC, improve application security — add rate limiting, implement CSRF protection, add input validation and sanitization, add security headers, and implement a password reset flow.
Using AI-DLC, make the application fully responsive with a mobile-first design approach, touch-friendly UI elements, hamburger menu for mobile, and optimized images for different screen sizes.
Brownfield Modernization
Using AI-DLC, convert the codebase from JavaScript to TypeScript — add type definitions for all components, define interfaces for API responses, add strict type checking, and maintain backward compatibility.
Using AI-DLC, implement comprehensive testing — unit tests for services with 80% coverage, integration tests for API endpoints, E2E tests for critical user flows, and test documentation.
Using AI-DLC, dockerize the application — create Dockerfiles for backend and frontend, add docker-compose for local development, configure environment variables, add health checks, and document the deployment process.
Using AI-DLC, add a product recommendation engine — "customers also bought" suggestions, similar products section, trending products widget, and recently viewed items.
CartService_modified.js. If you see duplicates, flag it.aidlc-state.md to see where you are at any point.