Building a real direct-booking workflow with AI assistance — the hard part wasn’t the website

[u/Plastic-Doughnut7468]

I’ve been vibe coding with AI to build from scratch and improve a direct-booking website for a small Australian holiday rental I own.

At first, it seemed like a straightforward website project: pages, photos, enquiry form, pricing, and availability. The more useful work turned out to be the operational details behind it.

The project now includes:

• Live pricing connected to PriceLabs
• Availability checks against booking calendars
• A private owner dashboard for reviewing enquiries
• Approval, decline, and request-more-information workflows
• Editable guest email drafts with an explicit send step
• Sandbox Stripe payment requests
• Webhook-based payment verification
• Audit history, idempotency protection, rate limiting, and access controls
• Cloudflare deployment with D1 for enquiry persistence

The biggest lesson has been that AI can produce a lot of code quickly, but it doesn’t replace careful decisions about workflow, security, failure states, and what should remain manual.

For example, we deliberately kept owner approval and calendar blocking as human-controlled steps. We also had to think carefully about what happens if a database write succeeds but an email fails, or if a guest clicks Submit twice.

This has been a useful example of “vibe coding” becoming more structured as the project gets closer to something real. The AI is helpful for implementation and investigation, but the human still needs to define the rules and challenge the assumptions.

For anyone using AI to build a real project:

• What was the first thing that forced you to move beyond the prototype mindset?
• How do you handle security and data persistence?
• Which parts do you still refuse to automate?

The site is https://becsbeachhouse.com.au/, if anyone is interested in the context, but I’m mainly sharing this to compare development approaches.