The AI Assistant can generate complete, detailed test cases in seconds. Just describe what you want to test, and the AI creates a fully-formed test case with steps, expected results, and tags.
Quick Start
Open the AI Chat
Press Cmd + K (Mac) or Ctrl + K (Windows/Linux)
Describe What to Test
Type your request in plain English: Create a test for user login with valid credentials
Review the Generated Test
The AI will create a complete test case with:
Clear title
Test steps with expected results
Preconditions
Tags
Priority
Save or Refine
Click “Save” to add it to your test suite
Or ask the AI to modify it: “Add a step for two-factor authentication”
Generation Patterns Single Test
Multiple Tests
From Requirements
From Documentation
Create one specific test: Create a test for password reset
Generate a test case for adding items to cart
Write a test for user profile update
The AI will generate a single, focused test case. Create a suite of related tests: Generate smoke tests for the checkout flow
Create regression tests for user authentication
Generate API tests for the products endpoint
The AI will create multiple test cases covering different scenarios. Generate from user stories or requirements: Create tests for this user story: As a user, I want to filter products by price range so that I can find items within my budget.
The AI will analyze the requirement and generate appropriate tests. Generate from API docs or specifications: Generate API tests from these docs: POST /api/users Creates a new user account Request Body: - email (required): string - password (required): string (min 8 chars) - name (optional): string Response: 201 Created
The AI will create tests covering all scenarios and edge cases. What Gets Generated When you ask the AI to create a test, it automatically generates:
Test Metadata
Unique identifier (TC-XXXX)
Clear, descriptive title
Appropriate priority (P0-P4)
Relevant tags
Test type (manual/automated)
Test Content
Preconditions
Detailed test steps
Expected results for each step
Overall pass/fail criteria
Test data (when applicable)
Best Practices
Follows naming conventions
Includes edge cases
Uses clear language
Atomic test design
Context Awareness
Matches your product type
Uses existing tags
Follows team patterns
Considers related tests
Example Prompts
Generate smoke tests for e-commerce checkout
AI generates:
Add item to cart
Update cart quantities
Apply discount code
Select shipping method
Enter payment information
Complete purchase
Receive confirmation email
Create API tests for user CRUD operations
AI generates:
Create user (valid data)
Create user (invalid email)
Create user (duplicate email)
Get user by ID
Update user information
Delete user
Verify deletion
Generate tests for mobile app onboarding
AI generates:
First launch experience
Permission requests
Account creation
Profile setup
Feature introduction screens
Skip onboarding flow
Complete onboarding
Create security tests for login
AI generates:
SQL injection attempts
XSS attack prevention
Brute force protection
Session fixation prevention
CSRF token validation
Password complexity enforcement
Account lockout after failures
Refining Generated Tests You can iterate with the AI to refine tests:
Ask for Modifications
Add a step to verify email notification is sent
Make this test cover mobile view as well
Split this into separate positive and negative tests
Request Different Formats
Make this more detailed with specific test data
Simplify this test to just the happy path
Convert this to an API test
Add Context
This is for a healthcare app, add HIPAA compliance checks
We use Stripe for payments, update the payment steps
Include accessibility testing requirements
Advanced Techniques Batch Generation
From Screenshots
Test Variations
Edge Cases
Generate many tests at once: Create a complete test suite for the shopping cart feature including: - Adding items - Updating quantities - Removing items - Cart persistence - Checkout initiation
The AI will create 10-15 related tests covering all aspects. Upload UI screenshots: Generate tests for this login screen [attach screenshot]
The AI analyzes the UI and creates appropriate tests. Generate test variations: Create the same login test but for: - Desktop web - Mobile web - iOS app - Android app
The AI creates platform-specific test cases. Focus on edge cases: What edge cases should I test for file upload?
The AI suggests and can generate tests for:
Empty file
File too large
Invalid file type
Special characters in filename
Network interruption
Concurrent uploads
Quality Assurance Review AI Output: Always review generated tests to ensure they match your specific requirements and context.
Provide Feedback: Tell the AI what to adjust: “Make step 3 more specific” or “Add assertions for response time”
Test Data: Be cautious with sensitive data. The AI generates sample data, but you should use appropriate test data for your environment.
Best Practices
Be Specific Instead of “create a login test,” try “create a test for login with OAuth via Google”
Provide Context Mention the feature, platform, or user story: “Create a test for the new multi-factor authentication feature on mobile”
Iterate Refine the test through conversation: “Add error handling scenarios” or “Include performance assertions”
Save Templates Once you get a good test format, save it as a template for consistency
What’s Next?
Search Your Tests Find tests using natural language
Ask Questions Get insights about your test suite
Organize Tests Use folders and tags effectively
Best Practices Advanced AI tips and techniques
