🚀 The Xano AI-Powered Backend Challenge: Human Refinement
I recently took on the Xano AI Challenge to build a production-ready e-commerce price tracker backend. While the Xano AI assistant provides an excellent starting foundation, the core logic for real-world functionality—like live price scraping and production-level security—required Human Refinement.
This post details how I refined the AI-generated backend to create a robust and functional Price Tracking API.
1. The AI Foundation
The Xano AI successfully established the foundational elements:
- Database Schema: It created the necessary tables, including a product table and a product_price_history table for tracking price c… [1:29 pm, 14/12/2025] Baby: --- tags: [xano, xanoai, backend, webscraping, ] ---
🚀 The Xano AI-Powered Backend Challenge: Human Refinement
I recently took on the Xano AI Challenge to build a production-ready e-commerce price tracker backend. While the Xano AI assistant provides an excellent starting foundation, the core logic for real-world functionality—like live price scraping and production-level security—required Human Refinement.
This post details how I refined the AI-generated backend to create a robust and functional Price Tracking API.
1. The AI Foundation
The Xano AI successfully established the foundational elements:
- Database Schema: It created the necessary tables, including a product table and a product_price_history table for tracking price changes over time.
- Core Endpoints: It generated basic CRUD (Create, Read, Update, Delete) endpoints for managing product data.
2. Human Refinement #1: The Live Web Scraping Logic
The major gap left by the AI was the ability to fetch live prices from external e-commerce websites. I solved this by creating a dedicated, public endpoint.
- New Endpoint: GET /get_prouct_details_live
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Web Scraping Implementation: Within the Function Stack, I added an External API Request function. This function takes an e-commerce URL as input.
- Logic: It uses the input url to fetch the raw HTML content of the product page.
- Data Storage: A subsequent Database Request function saves the extracted price and a current timestamp into the product_price_history table.
3. Human Refinement #2: Production Readiness & Security
To ensure the API is "production-ready," I implemented essential security and validation features:
- Input Validation: The endpoint requires a mandatory url input of type text. This ensures the API cannot be called without a target URL.
- Rate Limiting: To prevent misuse and secure the infrastructure, I implemented Rate Limiting on the get_prouct_details_live endpoint. This prevents any single user from making excessive scraping requests in a short period.
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🔗 Try the API (Swagger Documentation)
You can view the full documentation and test the get_prouct_details_live endpoint using the links below.
| Resource | Link |
|---|---|
| API Base URL | https://x8ki-letl-twmt.n7.xano.io/api:Kqp69FYE |
| Swagger Docs (OpenAPI) | (https://x8ki-letl-twmt.n7.xano.io/api:Kqp69FYE#/get_product_details_live/get_prouct_details_live%2Fget_product_details_live%7CGET URL-) |
This challenge was a fantastic opportunity to merge the power of AI-generated architecture with the necessary detailed logic of Human Refinement to build a truly production-ready backend.
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