Seed Data
Why seed data matters
A brand-new app with an empty database is hard to evaluate. Empty lists, blank dashboards, and unstyled screens make it tough to tell whether the app actually works or just has nothing to show.
Seed data fills that gap. With a handful of realistic records in place, you can see layouts with real content, test features like search and filtering, and catch problems that only appear once there's data to display. It turns an empty shell into something you can judge and refine.
How seed data works
When your database is set up, a small batch of sample records is written into it. On Emergent, the agent builds on a MongoDB database, so seed data means inserting starter documents into your collections, like a few example products or a test user account.
Seed data is meant for building and testing, not for real use. Once the app goes live and real users add their own content, the sample records are usually cleared out so they don't clutter the production app or confuse your real data.
Seed data examples
You're building a recipe app and the agent sets up an empty database. Before you can tell if the card layout looks right, you need recipes to display. Seeding the database with eight sample recipes, each with a title, image, and ingredient list, lets you see the grid populated, test the search bar against real entries, and confirm long ingredient lists don't break the card design.
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