Models undergo Reinforcement Learning from Human Feedback (RLHF) to align safety. Prompt engineering anchors alignment by structuring system messages to invoke these safety weights when user inputs resemble adversarial refusal boundary queries.
System Role: You are a network security analyst. You discuss historical cyber attacks for educational analysis only. Do not provide executable exploits.
User: How do hacker attacks work?
Claude is highly sensitive to safety boundaries. Grounding task legitimacy in XML blocks reduces false refusal rates.