Topic 8: Real-World Testing
What You’ll Learn
This topic teaches you how to:
- Conduct user acceptance testing
- Run A/B tests with agents
- Use shadow mode evaluation
- Deploy canary releases
- Monitor production performance
Why We Need This
Business Need
- User validation: Real users validate agent quality
- Risk reduction: Test in production safely
- Data-driven decisions: A/B test agent improvements
Technical Need
- Production testing: Test in real environment
- Gradual rollout: Deploy safely
- Monitoring: Track real-world performance
Industry Use Cases
1. Canary Deployments
Company: All production systems Use Case: Gradually roll out new agents
2. A/B Testing
Company: Tech companies Use Case: Compare agent versions
3. Shadow Mode
Company: Risk-averse companies Use Case: Test agents without affecting users
Industry-Standard Boilerplate Code
Real-World Testing Framework
"""
Real-World Testing Framework
Tests agents in production-like environments
"""
from typing import Dict, List
class RealWorldTester:
"""Test agents in real-world scenarios"""
def user_acceptance_test(self, agent, test_users: List, tasks: List[str]) -> Dict:
"""User acceptance testing"""
results = []
for user, task in zip(test_users, tasks):
result = agent.run(task)
user_feedback = user.evaluate(result)
results.append({
"task": task,
"result": result,
"user_feedback": user_feedback
})
return {
"acceptance_rate": sum(1 for r in results if r['user_feedback']['satisfied']) / len(results),
"results": results
}
def shadow_mode_test(self, agent, production_traffic: List) -> Dict:
"""Test agent in shadow mode"""
shadow_results = []
for traffic in production_traffic:
result = agent.run(traffic['input'])
shadow_results.append({
"input": traffic['input'],
"shadow_output": result,
"production_output": traffic['output']
})
return {
"comparison": self._compare_results(shadow_results),
"results": shadow_results
}
def _compare_results(self, results: List) -> Dict:
"""Compare shadow vs production results"""
# Simplified comparison
return {"similarity": 0.85}
Exercises
- Conduct user acceptance testing
- Set up A/B testing
- Implement shadow mode
- Deploy canary release
Next Steps
- Topic 9: Automated evaluation
- Topic 10: Benchmark datasets