Implementing Statistical Guardrails for Non-Deterministic Agents

# AI Systems That Give Different Answers Need Safety Checks Some AI systems produce different results every time you ask them the same question, which can be unpredictable and risky in real-world applications. The article explains how to add statistical safeguards—essentially built-in consistency checks—to catch when these systems start behaving erratically or producing unreliable outputs. This matters because it helps ensure AI you rely on for decisions stays trustworthy and doesn't suddenly change its answers for no good reason.