AI Guardrails

💬 In plain words: An AI guardrail is only proven when it survives a direct attack. To test a limit properly, you must hit it with six different angles of persuasion. If the AI holds its ground against all six, you have a solid control. If it fails even one, your "guardrail" was actually just a polite suggestion. 📌 Real-Life Example: A company named Meridian wanted to test an AI agent's ceiling for issuing goodwill credits. They attacked the AI using six angles: customer loyalty, competitor pricing, social proof, a threat to cancel, a fake manager approval, and a direct prompt override. The AI denied the credit every time. Because all six held, the limit was proven secure.

💬 In plain words: An instruction tells an AI model what it should do. A filter (or guardrail) controls what an AI model can do. A determined user can always manipulate an AI into ignoring what it "should" do, but nobody can bypass hard-coded system filters that dictate what it "can" do.