A Simple Request Sparks a Technical Challenge

While helping his 12-year-old son prepare for the school year, a developer identified a surprising gap in Amazon's consumer interface. The child wanted to send his current shopping cart contents to a friend so they could coordinate their supply purchases. Despite Amazon offering such features for business accounts, there was no straightforward way for individual shoppers to share a cart without creating a registry or moving items to a list.


Finding this limitation counterintuitive, the father decided to see if he could build a solution himself using modern AI tools. As he noted: «I'm always looking for a reason to build something, but I really wondered if it would be possible to build something like this.»


The Power and Illusion of 'Vibe Coding'

Leveraging AI-driven development—often referred to as 'vibe coding'—the developer described the problem to ChatGPT. He requested a tool capable of reading Amazon cart contents, generating a private link, and allowing a recipient to view the items. Within a short period, the AI had produced a functional website and a Chrome extension interface.


The resulting prototype was impressive in its presentation. Key features included:

  • No requirement for user accounts or database storage.
  • Data encoded directly into the shareable link.
  • Privacy-focused design that avoided handling sensitive Amazon passwords or payment data.

Technical Realities vs. AI Prototypes

While the interface appeared fully functional, the developer hit a significant roadblock when attempting to automate the transfer of items into the friend's cart. The prototype’s attempt to use specific Amazon URLs to inject products resulted in server errors. Amazon’s security and backend structure do not support direct cart population from third-party links.


This experience served as a lesson in the limitations of AI development. The developer explained the realization:

«It was a useful reminder of how deceptive vibe coding can be, even when nobody is trying to deceive anyone. AI can produce a polished interface before the underlying behavior has been properly tested.»

Future Outlook

While the tool couldn't achieve a perfect 'one-click' transfer, the project successfully demonstrated how a shared view of products could still be helpful for coordination. Moving forward, the developer suggests that a more robust version could potentially add items to a cart by mimicking user interactions, though such a tool would require constant maintenance to keep pace with Amazon’s website updates.


Ultimately, the experiment proved that while AI can rapidly bridge the gap between a concept and a functional prototype, transitioning to a stable, production-ready product remains a complex challenge that requires navigating corporate technical boundaries.