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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:

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

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

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

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:

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 base updates

Quality Metrics

Track these metrics:

MetricTargetAction if Below
Accuracy> 90%Review knowledge base
Response Time< 3sOptimize queries
User Satisfaction> 4.0/5Review 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:

  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

Tools & Resources


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 →