Guardrails, Safety, and Handling Hallucinations

Every LLM-powered system needs guardrails: mechanisms that catch or prevent bad outputs before they reach a user or trigger a real-world action. This matters even more for agents, since a hallucinated tool call can mean a real action taken with wrong data. Practical guardrails include input validation (rejecting or sanitizing unexpected user input), output v...