Safety Testing Sandbox
Test AI agents safely in isolated environments before production deployment
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0 / 5 completedWhy Safety Testing Matters
Before deploying AI agents to production, you must rigorously test their safety, reliability, and failure modes. A sandbox environment provides a controlled space to challenge agents with adversarial inputs, simulate failures, test boundaries, and validate guardrails—without risking real users, data, or systems. Think of it as a proving ground where agents can fail safely so they won't fail dangerously in production.
🎯 Test Boundaries
See what happens when agents hit permission limits or capability edges
💣 Break Things Safely
Cause failures intentionally to understand failure modes
🛡️ Validate Guardrails
Ensure safety mechanisms actually prevent harmful behavior
📈 Build Confidence
Deploy with certainty that agents can handle edge cases
Interactive: Explore Safety Testing Layers
Click each layer to understand essential safety testing components:
Don't wait until production to discover safety issues. Build sandbox testing into your development workflow from day one. Every new capability, every prompt change, every guardrail update should be tested in isolation first. The cost of fixing issues in a sandbox is infinitely lower than the cost of production incidents.