The output (used by the user interface) is a JSON schema (DSL) which defines the whole app (collections, fields, relations, pages, access/roles menu etc). It can be changed throughout the lifetime of the application. The built-in revision control makes it easy to revert changes.
In the article (link below) the author vibe-coded a full-stack React “todo” app with an Claude Code and had it live on the internet in under 90 seconds — including frontend, backend, database, REST API, Swagger docs, and deployment — without writing a single line of code by hand.
The key takeaway isn’t just the speed. What made the rapid turnaround possible was the stack itself: a low-ceremony platform (Codehooks.io) that keeps frontend and backend together, avoids CORS and infra config, and uses schema-driven APIs so the AI doesn’t get stuck on peripheral problems.
Instead of AI nirvana, the article argues we should be thinking about what stacks maximize AI productivity — the ones that remove friction points and keep the feedback loop tight between idea and deployment.
The output (used by the user interface) is a JSON schema (DSL) which defines the whole app (collections, fields, relations, pages, access/roles menu etc). It can be changed throughout the lifetime of the application. The built-in revision control makes it easy to revert changes.