As more teams adopt AI-driven agents within Salesforce, we’re seeing new testing complexities that go well beyond traditional QA.
Some unique challenges I’ve come across:
✅ Ensuring data validation with unpredictable prompts
✅ Testing for goal alignment and preventing hallucinations
✅ Managing multi-agent workflows
✅ Verifying ethical compliance and bias prevention
✅ Scaling tests to cover real-world usage scenarios
Even with tools like Agentforce Testing Center and manual testing via Agent Builder, some gaps still exist — like validating full conversational flows, not just isolated prompts.
What’s been your biggest challenge with testing AI agents in Salesforce (or similar platforms)?
Is it around data integrity, scale, compliance — or something else entirely?
Would love to hear your experiences or insights.
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