We Simulated 5,400 AI Agent Scenarios. Here Is What Broke.
Your AI agent passes every unit test. It handles demo scenarios perfectly. Then it goes to production in a regulated industry and recommends a solvency ratio that violates Vietnamese insurance law, or bypasses an approval chain that exists for compliance reasons, or confidently cites a regulation that was repealed two years ago.
The problem isn't that your agent is broken. The problem is that nobody tested the scenarios that matter — the regulatory edge cases, the cross-role handoffs, the adversarial inputs that exploit domain-specific knowledge gaps.
We built a system that generates these scenarios automatically from enterprise ontologies, then ran 5,400 simulations across 3 LLM models and 5 regulated industries. Here's what we learned about verifying AI agents before they touch production.