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.

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Testing Pyramid

Test at multiple levels:

1. Unit Tests - Individual components (30% of tests)
2. Integration Tests - Agent + tools + knowledge (50% of tests)
3. End-to-End Tests - Full user workflows (20% of tests)

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Pre-Deployment Testing

1. Basic Functionality

   Test that the agent understands its role:

   • Ask “What can you help me with?”
   • Verify it describes its capabilities correctly

2. Happy Path Scenarios

   Test common, expected use cases:

   • Typical customer questions
   • Standard workflows
   • Normal inputs

3. Edge Cases

   Test unusual but valid scenarios:

   • Empty inputs
   • Very long inputs
   • Special characters
   • Multiple languages

4. Error Handling

   Test how agent handles problems:

   • Invalid inputs
   • Missing information
   • System errors
   • Timeout scenarios

5. Boundary Testing

   Test limits:

   • What agent should NOT do
   • Escalation triggers
   • Permission boundaries

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Test Categories

1. Accuracy Tests

Goal: Verify correct answers

Test: "What is your pricing?"
Expected: Accurate pricing information with link
Actual: [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 response
Actual: [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 team
Actual: [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 policy
Actual: [Agent response]
Pass/Fail: ✅

Check for:

• No data leakage
• Proper authentication
• Permission respect
• PII protection

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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

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Automated Testing

Set up automated tests that run on every change:

test-suite.yml

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 updates

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Quality Metrics

Track these metrics:

Metric	Target	Action if Below
Accuracy	> 90%	Review knowledge
Response Time	< 3s	Optimize queries
User Satisfaction	> 4.0/5	Review conversations
Escalation Rate	< 20%	Improve knowledge
Error Rate	< 5%	Fix bugs, improve handling

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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

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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

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Beta Testing

Before full launch:

1. Internal Beta (1 week)

   • Test with your team
   • Gather feedback
   • Fix critical issues

2. Limited Beta (1-2 weeks)

   • Deploy to 10% of users
   • Monitor closely
   • Iterate quickly

3. Expanded Beta (1-2 weeks)

   • Deploy to 50% of users
   • Track metrics
   • Final refinements

4. Full Launch

   • Deploy to 100%
   • Continue monitoring
   • Ongoing optimization

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Tools & Resources

• Test Console - Built-in testing interface
• Run agents via API - Run tasks programmatically
• Usage & Billing - Track usage and performance

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Next Steps

1. Create your test plan
2. Write test scenarios
3. Set up automated tests
4. Run beta testing
5. Monitor in production

Start testing your agent →