The probability that an agent succeeds on the same task k times in a row. It measures reliability, which a single successful run cannot show.

Should I test against real production systems?

No. Always sandbox with fake data and reversible actions. Testing against production risks real side effects.

ModelRefs / Test an AI Agent Safely

Test an AI Agent Safely

Test an AI agent for real: verify outcomes not just final answers, score the trajectory, measure reliability, sandbox it, and red-team for unsafe actions.

What this reference supports

Test an AI Agent Safely: This tutorial provides a structured implementation path with prerequisites, steps, checkpoints, and related references. Read the complete sequence before applying commands or configuration in production.

Test an AI Agent Safely: Adapt examples to the versions, security boundaries, data policy, and failure-handling requirements of your system. Validate intermediate outputs and keep a rollback path for changes that affect users or stored data.

Test an AI Agent Safely: Tutorial examples demonstrate a technique; they do not prove reliability, compliance, performance, or suitability for a workload. Use current primary documentation and test the final system under representative conditions.

Continue your research

Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Test an AI Agent Safely.