How to Generate a Backend with AI
Generating APIs, authentication and a database with AI: how to describe your data model, what gets produced, and how to test it from the frontend.
Zusagi TeamPublished Updated 7 min readDescribe entities and rules, not tables
Tell the AI what exists and how it relates: "teams have members; members create invoices; only owners can delete". The generator turns that into a schema, relations, endpoints and permission checks. You rarely need to name columns yourself.
What a generated backend contains
Expect a database schema with migrations, REST endpoints for each entity and action, authentication with sessions and roles, validation, and integration hooks for services such as payments or email. Zusagi produces this as readable server code you can inspect. Details are on the AI backend generator page.
Test through the frontend
The fastest way to validate a backend is to use the frontend that calls it. Because Zusagi plans both layers together, the preview exercises the real endpoints. Describe failures ("saving an invoice returns an error") and the fix is applied to the right layer.
Deploying the backend
Deployment includes the database, the API and environment configuration. On Zusagi this is part of publishing a build, available on Pro and Max plans.