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Testing
2 hrs
MVPUnder 5 prompts to build
Klevergood
We wanted to test our AI development framework on something we had never done before: an ecommerce site. The results were stunning.
The problem
We needed to stress-test our development framework on an unfamiliar domain. We had built SaaS tools, dashboards, and content platforms. But we had never touched ecommerce. Could our AI-powered workflow handle product catalogs, carts, checkout, and inventory?
What we built
A fully functional ecommerce storefront with product listings, filtering, cart management, and checkout flow. The entire site was generated from fewer than 5 prompts and was production-ready in under 2 hours.
The experiment proved the framework works across domains. The same methodology that builds SaaS tools builds storefronts.
Screenshots
Features
What it does
Full storefront
Product listings, filtering, detail pages, cart, and checkout flow.
AI-generated frontend
Entire UI generated from fewer than 5 prompts using our development framework.
Inventory management
Real-time stock tracking connected to the product catalog.
Order processing
Complete purchase flow with confirmation emails and order history.
Framework validation
Proved our AI development methodology works across unfamiliar domains.
Process
How we built it
1
Selected ecommerce as the test domain
Deliberately chose something outside our expertise to test framework flexibility.
2
Wrote the initial prompt
Described the store concept, product categories, and desired user flow in a single detailed prompt.
3
Generated the full storefront
AI produced the complete frontend: product grid, detail pages, cart, and checkout flow.
4
Added backend integration
Connected to Supabase for product data, inventory tracking, and order management.
5
Validated with real products
Loaded actual product data and ran through the full purchase flow end to end.
Reflections
What we took away from this project.
What went wrong
The initial product page layout was too generic. Ecommerce has specific UX patterns (size selectors, image zoom) that needed manual refinement.
What went right
The framework handled the domain switch without any structural changes. The same prompting approach that builds dashboards builds storefronts.
What we learned
AI development frameworks need to be domain-agnostic. If your methodology only works for one type of product, it's not a methodology. It's a template.
Want something like this for your business?
Tell us what you're working on. We'll tell you how fast we can build it.
