Duration: 2-3 hours | Build a product catalog system using AI-DLC methodology
Apply AI-DLC methodology to build an e-commerce product catalog. Customers can browse products, search, view details, and add items to cart. Admins can manage products and inventory.
You kick off the entire workflow with a single prompt describing what you want to build. AI-DLC Workflow takes it from there.
Open a new chat and type:
Using AI-DLC, build a product catalog system where customers can browse products, search, view details, and add items to cart. Admins can manage products and inventory.
AI-DLC Workflow activates, displays a welcome message, scans your workspace, sets up aidlc-docs/, and proceeds to the next stage.
The AI analyzes your request and asks clarifying questions about anything unclear. You'll also see a question about enabling security extension rules.
When the AI presents the questions file: Open it, fill in your [Answer]: tags. For the security extension question, answer "No" since this is a prototype. Then tell the AI:
I have answered the clarification questions. Please re-read the file and proceed.
The AI may ask follow-up questions. Once resolved, it generates a requirements document.
The AI creates user stories that become the contract for what gets built. It runs in two parts: first it plans how to structure the stories, then it generates them with personas and acceptance criteria.
Part 1 — Planning: The AI creates a story generation plan with questions. Open the plan file, fill in your answers, then tell the AI you're done.
Part 2 — Generation: The AI executes the plan step by step, marking checkboxes as it goes.
Go to aidlc-docs/aidlc-state.md, find the first unchecked item, then go to the corresponding plan file and resume from that point. For shorter workshops, you can skip this and continue in the same chat.The AI determines which Construction stages to run and decomposes the system into multiple units that can be built independently. Units are ordered so everything is built properly.
If you want deployment and Infrastructure Design is marked SKIP:
Add Infrastructure Design to the plan. We need deployment to AWS.
AI-DLC Workflow designs the detailed component model — all components, data models, APIs, and how they interact. No code yet.
The main build activity. AI-DLC Workflow's Construction phase has a built-in per-unit loop — for each unit of work, it runs design and code generation stages in sequence, completing each unit fully before moving to the next. The approval gate after each unit says "Continue to next unit" or "Proceed to Build & Test." This is less explicit than a manual tracker (like the one in the Copy-Paste Prompts tab), but the workflow handles the cycling automatically.
Part 1 — Planning: The AI creates a code generation plan with numbered, checkboxed steps.
Part 2 — Generation: The AI implements each unit, tests it, validates integration, and marks it complete before moving to the next.
The AI designs the AWS deployment architecture, creates infrastructure as code for all resources, and deploys to us-west-2.
AI-DLC Workflow generates build and test instructions. Verify the deployed application works end-to-end.
AI-DLC Workflow's Operations phase is a placeholder for future expansion. This is a group discussion.
Discuss as a group:
Now that we've built and deployed our product catalog, discuss how AI would help with: 1. Adding product recommendations 2. Implementing user authentication 3. Adding an analytics dashboard 4. Scaling during high-traffic events Please explain how this would work for our specific application.
[Answer]: tags, then tell the AI to re-read.aidlc-state.md. For short workshops, you can often skip this.aidlc-state.md to see where you are at any point.We will work on building an application today. For every front end and backend component we will create a project folder. All documents will reside in the aidlc-docs folder. Throughout our session I'll ask you to plan your work ahead and create an md file for the plan. You may work only after I approve said plan. These plans will always be stored in aidlc-docs/plans folder. You will create many types of documents in the md format. Requirement, features changes documents will reside in aidlc-docs/requirements folder. User stories must be stored in the aidlc-docs/story-artifacts folder. Architecture and Design documents must be stored in the aidlc-docs/design-artifacts folder. All prompts in order must be stored in the aidlc-docs/prompts.md file. Confirm your understanding of this prompt. Create the necessary folders and files for storage, if they do not exist already.
Intent: Build a product catalog system where customers can browse products, search, view details, and add items to cart. Admins can manage products and inventory. Do not propose solutions yet. Acknowledge the intent and confirm understanding.
Your Role: You are an expert product manager with e-commerce domain expertise. Before you start the task as mentioned below, please do the planning and write your steps in the aidlc-docs/plans/user_stories_plan.md file with checkboxes against each step in the plan. List your Deliverables in the plan. If any step needs my clarification, please add it to the step to interact with me and get my confirmation. Do not make critical decisions on your own. Once you produce the plan, ask for my review and approval. After my approval, you can go ahead to execute the same plan one step at a time. Once you finish each step, mark the checkboxes as done in the plan. Your Task: Build comprehensive user stories for the product catalog system based on the intent. Include customer-facing features (browsing, search, cart) and admin features (product management, inventory). Write the user stories to aidlc-docs/story-artifacts/user_stories.md
I reviewed the plan. Please proceed with the approved approach.Your Role: You are an experienced software architect. Before you start the task as mentioned below, please do the planning and write your steps in the aidlc-docs/plans/units_plan.md file with checkboxes against each step in the plan. If any step needs my clarification, please add it to the step to interact with me and get my confirmation. Do not make critical decisions on your own. Once you produce the plan, ask for my review and approval. After my approval, you can go ahead to execute the same plan one step at a time. Once you finish each step, mark the checkboxes as done in the plan. Your Task: Group the user stories in aidlc-docs/story-artifacts/user_stories.md into multiple units that can be built independently. Each unit contains highly cohesive user stories that can be built by a single team. The units are loosely coupled with each other. For each unit, write the respective user stories and acceptance criteria. Write the units to aidlc-docs/story-artifacts/units.md
Your Role: You are an experienced software architect and engineer. Before you start the task as mentioned below, please do the planning and write your steps in the aidlc-docs/plans/domain_model_plan.md file with checkboxes against each step in the plan. List your Deliverables in the plan file. If any step needs my clarification, please add it to the step to interact with me and get my confirmation. Do not make critical decisions on your own. Once you produce the plan, ask for my review and approval. After my approval, you can go ahead to execute the same plan one step at a time. Once you finish each step, mark the checkboxes as done in the plan. Your Task: Design the domain model to implement all the user stories. This model shall contain all the components, the data models, the APIs, and how the components interact to implement the user stories. The components should be at a business level, do not generate any code yet. Write the domain model into aidlc-docs/design-artifacts/domain_model.md
Your Role: You are an experienced software engineer. Your Task: 1. Review the units in aidlc-docs/story-artifacts/units.md 2. Create a file aidlc-docs/plans/unit_implementation_tracker.md with: - Total number of units - List of all units with checkboxes (unchecked) - Suggested implementation order Format: # Unit Implementation Tracker Total Units: X ## Implementation Order - [ ] Unit 1: [Name] - [Brief description] - [ ] Unit 2: [Name] - [Brief description] - [ ] Unit 3: [Name] - [Brief description] ... Show me the tracker file.
Your Task: Look at aidlc-docs/plans/unit_implementation_tracker.md and implement the next unchecked unit. 1. Implement ONLY that unit from aidlc-docs/story-artifacts/units.md 2. Refer to the domain model in aidlc-docs/design-artifacts/domain_model.md 3. Build data models, backend APIs, and frontend components for this unit 4. Ensure all previously implemented units still work 5. Mark the unit as complete in the tracker by checking the checkbox Tell me which unit you're implementing before you start.
Test the unit you just implemented: 1. Test this unit's functionality 2. Test integration with all previous units 3. Verify all user stories in this unit work Show me: - Test results - Updated tracker showing this unit checked off - How many units remain Fix any issues before proceeding to the next unit.
Your Task: All units in aidlc-docs/plans/unit_implementation_tracker.md should now be checked off. Run comprehensive end-to-end tests. Test: 1. All units work independently 2. All integrations work correctly 3. Complete user flows work end-to-end 4. All user stories are satisfied Show me complete test results and the final tracker with all units checked.
Your Role: You are an experienced Cloud Architect. Before you start the task as mentioned below, please do the planning and write your steps in the aidlc-docs/plans/deployment_plan.md file with checkboxes against each step in the plan. List your Deliverables in the plan file. If any step needs my clarification, please add it to the step to interact with me and get my confirmation. Do not make critical decisions on your own. Once you produce the plan, ask for my review and approval. After my approval, you can go ahead to execute the same plan one step at a time. Once you finish each step, mark the checkboxes as done in the plan. Your Task: Deploy the application to AWS. Create infrastructure as code for all resources. Deploy to us-west-2 region.