Learn how to leverage batch testing, AI-generated synthetic scenarios, monitoring and observability capabilities to ensure accuracy and trust before Agentforce agent deployment.
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Built to Scale: Agentforce Quality via Testing Center
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, CTO, Aethereus
, Head of AI & Data Solutions, Myridius
Role: Administrator
Product: Agentforce
Topic: Agentic AI
Session Level: Intermediate
Session Type: Theater
Session Summary: The session showcased the capabilities of the Testing Center, emphasizing its role in simplifying and enhancing AI testing workflows. Key features included AI-generated test cases from natural language prompts or CSV uploads, secure sandbox execution for realistic testing, and batch testing for large-scale scenarios. Detailed event logging and observability were highlighted as critical for ensuring the accuracy, safety, and reliability of generative AI outputs, with human oversight playing a pivotal role in quality assurance. By enabling parallel test execution, debugging with granular logs, and iterative improvement through templates, the Testing Center ensures robust testing processes, saving time and preventing issues before customer interactions occur.
Key Takeaways:
• AI-generated test cases allow users to create tailored scenarios using natural language prompts or CSV uploads, improving flexibility and efficiency in testing.
• Secure sandbox execution replicates production environments, ensuring realistic testing conditions and minimizing risks before deployment.
• Detailed event logging and observability provide transparency into agent behavior, enabling rapid debugging and fostering trust in generative AI outputs.
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