When building new applications, one of the first hurdles I run into is testing with real-looking data. Empty databases don’t tell you much, and hardcoding “User1, User2” everywhere gets old fast. That’s where ChatGPT has become one of my favorite tools — it helps me generate realistic seed data quickly and in whatever format I need: JSON, CSV, or SQL insert statements.
This has saved me countless hours when mocking APIs, populating test environments, or demoing projects to stakeholders. Let me show you a few ways I use it.
Example 1: JSON Seed Data
If I’m working on an API that returns users, I can ask ChatGPT:
“Generate 5 fake users in JSON format with realistic names, emails, and roles.”
And I get:
[
{
"id": 1,
"name": "Samantha Green",
"email": "samantha.green@example.com",
"role": "Admin"
},
{
"id": 2,
"name": "David Torres",
"email": "david.torres@example.com",
"role": "Editor"
},
{
"id": 3,
"name": "Emily Zhang",
"email": "emily.zhang@example.com",
"role": "Viewer"
},
{
"id": 4,
"name": "Marcus Johnson",
"email": "marcus.johnson@example.com",
"role": "Editor"
},
{
"id": 5,
"name": "Olivia Reed",
"email": "olivia.reed@example.com",
"role": "Viewer"
}
]
Perfect for mocking frontend components or simulating API responses.
Example 2: SQL Insert Statements
Sometimes I want to seed a local database. Instead of typing out rows manually, I ask ChatGPT:
“Generate SQL insert statements for a Products table with 5 sample rows (id, name, price, in_stock).”
INSERT INTO Products (id, name, price, in_stock) VALUES (1, 'Wireless Mouse', 24.99, true), (2, 'Mechanical Keyboard', 89.50, true), (3, 'USB-C Hub', 39.99, false), (4, 'Noise-Canceling Headphones', 129.00, true), (5, '4K Monitor', 349.99, true);
That’s instantly usable in my seed script.
Example 3: CSV for Bulk Imports
Need to simulate bulk data? I’ll ask:
“Generate a CSV file with 10 rows of orders: OrderId, CustomerName, Item, Quantity, Total.”
OrderId,CustomerName,Item,Quantity,Total 1001,Michael Carter,Laptop,1,999.99 1002,Sarah Lopez,Smartphone,2,1499.98 1003,Daniel Smith,Tablet,1,299.99 1004,Ana Martins,Headphones,3,357.00 1005,James Allen,Smartwatch,1,199.99 1006,Rachel Kim,Keyboard,2,180.00 1007,Luis Ramirez,Monitor,1,349.99 1008,Emma Scott,Wireless Mouse,2,49.98 1009,Kevin Brown,External SSD,1,129.00 1010,Nina Johnson,USB-C Dock,1,89.99
I can save this straight into a .csv file and import it into my system.
Why I Love This Approach
- Saves Time – No more typing filler data by hand.
- Realistic Outputs – Names, emails, and values feel authentic, which helps when demoing apps.
- Flexible Formats – JSON, SQL, CSV, YAML — whatever I need, I can get.
- Customizable – I can request data that fits my domain (e.g., medical records, ecommerce, education).
Final Thoughts
Seed data may not be glamorous, but it’s crucial for development. Using ChatGPT, I can generate realistic, structured datasets in minutes. Whether I need a few rows for a demo or hundreds for stress testing, it’s become one of my go-to shortcuts.
If you’re tired of staring at empty tables or repeating User1, give this a try — you’ll never look back.