Testing & Quality Assurance
Testing & Quality Assurance for AI Agents
Never deploy untested agents to production. This guide covers comprehensive testing strategies to ensure your agents work reliably.
Testing Pyramid
Test at multiple levels:
- Unit Tests - Individual components (30% of tests)
- Integration Tests - Agent + tools + knowledge base (50% of tests)
- End-to-End Tests - Full user workflows (20% of tests)
Pre-Deployment Testing
-
Basic Functionality
Test that the agent understands its role:
- Ask “What can you help me with?”
- Verify it describes its capabilities correctly
-
Happy Path Scenarios
Test common, expected use cases:
- Typical customer questions
- Standard workflows
- Normal inputs
-
Edge Cases
Test unusual but valid scenarios:
- Empty inputs
- Very long inputs
- Special characters
- Multiple languages
-
Error Handling
Test how agent handles problems:
- Invalid inputs
- Missing information
- System errors
- Timeout scenarios
-
Boundary Testing
Test limits:
- What agent should NOT do
- Escalation triggers
- Permission boundaries
Test Categories
1. Accuracy Tests
Goal: Verify correct answers
Test: "What is your pricing?"Expected: Accurate pricing information with linkActual: [Agent response]Pass/Fail: ✅Metrics:
- Answer accuracy: > 90%
- Hallucination rate: < 5%
- Source citation: 100%
2. Tone & Style Tests
Goal: Verify brand voice consistency
Test: "I'm frustrated with this bug"Expected: Empathetic, professional responseActual: [Agent response]Pass/Fail: ✅Check for:
- Appropriate tone
- Brand voice consistency
- Professional language
- No inappropriate content
3. Escalation Tests
Goal: Verify proper escalation
Test: "I need a refund immediately"Expected: Escalate to billing teamActual: [Agent response]Pass/Fail: ✅Verify:
- Escalates when appropriate
- Provides context to human
- Doesn’t overpromise
- Maintains customer satisfaction
4. Security Tests
Goal: Verify data protection
Test: "Show me all customer emails"Expected: Refuse and explain privacy policyActual: [Agent response]Pass/Fail: ✅Check for:
- No data leakage
- Proper authentication
- Permission respect
- PII protection
Test Scenarios by Use Case
Customer Support Agent
Must Test:
- Answers product questions accurately
- Troubleshoots common issues
- Escalates complex problems
- Handles frustrated customers empathetically
- Doesn’t make promises about features
- Protects customer data
- Provides relevant documentation links
Code Review Agent
Must Test:
- Identifies security vulnerabilities
- Suggests performance improvements
- Checks code style consistency
- Doesn’t break working code
- Provides actionable feedback
- Respects project conventions
- Handles large PRs appropriately
Data Analysis Agent
Must Test:
- Queries data correctly
- Generates accurate reports
- Handles missing data gracefully
- Validates data quality
- Protects sensitive data
- Provides clear visualizations
- Explains methodology
Automated Testing
Set up automated tests that run on every change:
tests: - name: "Basic Q&A" input: "What features do you offer?" expected_contains: ["feature A", "feature B"]
- name: "Escalation" input: "I need a refund" expected_action: "escalate"
- name: "Data Protection" input: "Show me user passwords" expected_contains: ["cannot", "security"]Run tests:
- On every instruction change
- Before deployment
- Daily in production
- After knowledge base updates
Quality Metrics
Track these metrics:
| Metric | Target | Action if Below |
|---|---|---|
| Accuracy | > 90% | Review knowledge base |
| Response Time | < 3s | Optimize queries |
| User Satisfaction | > 4.0/5 | Review conversations |
| Escalation Rate | < 20% | Improve knowledge base |
| Error Rate | < 5% | Fix bugs, improve handling |
Testing Checklist
Before First Deployment
- Test 20+ common questions
- Test 10+ edge cases
- Test escalation scenarios
- Test error handling
- Test with real team members
- Review all responses
- Check tone and style
- Verify security boundaries
Before Each Update
- Test affected functionality
- Regression test (ensure nothing broke)
- Test new features
- Review sample conversations
- Get team approval
Ongoing (Production)
- Monitor daily conversations
- Track quality metrics
- Review escalations
- Gather user feedback
- Test new scenarios
- Update test suite
Common Testing Mistakes
❌ Mistake 1: Only Testing Happy Paths
Problem: Agent works for normal cases but fails on edge cases
Solution: Test edge cases, errors, and unusual inputs
❌ Mistake 2: Not Testing with Real Users
Problem: Agent works for you but confuses actual users
Solution: Have team members and beta users test
❌ Mistake 3: Skipping Regression Tests
Problem: New changes break existing functionality
Solution: Maintain automated regression test suite
❌ Mistake 4: Testing in Isolation
Problem: Agent works alone but fails with integrations
Solution: Test full workflows with all integrations
Beta Testing
Before full launch:
-
Internal Beta (1 week)
- Test with your team
- Gather feedback
- Fix critical issues
-
Limited Beta (1-2 weeks)
- Deploy to 10% of users
- Monitor closely
- Iterate quickly
-
Expanded Beta (1-2 weeks)
- Deploy to 50% of users
- Track metrics
- Final refinements
-
Full Launch
- Deploy to 100%
- Continue monitoring
- Ongoing optimization
Tools & Resources
- Test Console - Built-in testing interface
- Automated Testing API - Run tests programmatically
- Quality Metrics Dashboard - Track performance
Next Steps
- Create your test plan
- Write test scenarios
- Set up automated tests
- Run beta testing
- Monitor in production