Cabbin
Made for
Cabbin
Location
Dubai, UAE
Year
2026
what it is
Cabbin is an AI-native marketplace inspired by real needs and behaviors I observed during my years in aviation. I’m using AI to take the whole product from concept through strategy, design, and vibe-coded implementation - turning an idea into a working MVP. Let me tell you about it.
Shopping local, but anywhere
Cabbin (as in Cabin Crew) is - you’ve guessed it - totally inspired by the aviation lifestyle. During my own time in #crewlife, I discovered a cool little privilege of living borderless: real frequent travelers have their own way of shopping local. They get their groceries from Germany, their cosmetics from Korea, their beachwear from Brazil, their supplements from Australia. I think that’s fabulous. And I want to let everyone in on it.
So I started building Cabbin: a community marketplace where frequent travelers can bring back and share their favorite finds from around the world. And why have things shipped halfway around the world by a company, if someone is going there anyway?
For now, Cabbin is invite-only, because the MVP is built around the very thing that makes this idea work: community and trust.
BUILDING CABBIN
The obsessive animal in me wouldn’t start building a single thing without carefully defining the scope first. This was as much for the AI as it was for myself, as I wanted to maintain a record of good enough product context to make good decisions throughout.
The idea was to create a Project Knowledge base. I wrote an MVP Spec Sheet to map out absolutely all the V1 features and flows, including Admin actions and Analytics Dashboard. Yes, I’m thinking about the metrics I’d want to track for future iterations. AI sort of tricked me into writing additional documentation, like the architecture, data model, request state machine, API behaviors and database schema. I fed all these into the Knowledge Base. Some of it turned out useful, some of it became obsolete surprisingly quickly. You build and you learn.
I also defined my initial tool stack, knowing full well these choices could become fluid. I committed to Lovable for the build, as its Supabase integration would make the chat functionality easier to implement. I used GitHub, Claude Design, Claude Code, ChatGPT, and Figma.
SUPER TIDY AI-NATIVE DESIGN SYSTEM
I knew right away I wanted to have full control of Cabbin’s UX and UI, so I started with design. After defining the Information Architecture for the responsive web platform, I designed a few key screens and empty states - just enough to establish the foundations of my Design System. I then used an MCP workflow to translate this design context from Figma Variables to machine-readable design tokens in CSS.
But I had a bigger ambition for the Design System: I didn’t want it to belong to Lovable, or even to Cabbin’s app codebase. I wanted a tool-agnostic (but not framework-agnostic), AI-native system that any AI agent (or human) could pick up, read, use, test, and scale.
So I built the repo architecture itself around this concept. The Design System lives in its own independent repo containing its principles, React + Tailwind implementation rules, AI instructions, tokens, components, and testing playground (storybook). The Cabbin app then consumes this repo, rather than owning it.
Also, in the spirit of not reinventing the wheel, I wanted my system to be built on Google’s Material 3 Expressive principles. That means I review, fix, test, and implement each new component as I build them, scaffolding the Design System as I go. If I had to describe it, I’d say “Cabbin is a React Design System based on Material 3 Expressive principles, implemented with Tailwind CSS and Cabbin-owned tokens”. If we ever meet, I’ll be proud to tell you all about it.
SCOPE INTO SPRINTS
With the foundations in place, and using AI to help me think through the dependencies, I landed on a sequence of 11 Epics covering the entire Cabbin experience, from Pre-Authentication, Onboarding & Account Activation through the Dashboard, Authenticated Flows, Notifications, and Admin.
The plan is to turn each Epic into a mega-prompt for Lovable, with enough product context, functionality overview, user stories, acceptance criteria, error states, and instructions for using reusable components. This has worked really well for the first sprints.
So that’s Cabbin, for now. You’ll currently find me tightening the Design System before I let the rest of the product loose. Cabbin started with an observation from my life in aviation. It has turned into a product, a design system, an AI-native workflow, and a rather ambitious experiment in how much one curious designer can actually make.
