How to Install Guardrails for Your AI Agents with CrewAI | by Alessandro Romano | January, 2025

LLM Agents are non-judgmental in nature: use the appropriate guidelines for your AI program

Given the undefined nature of LLMs, it's easy to end up with an output that doesn't fully match our intended application. A well-known example is Tay, a Microsoft chatbot that famously started sending offensive tweets.

Whenever I am working on an LLM application and want to decide if I need to implement additional security techniques, I like to focus on the following points:

• Content Security: Reduce the risk of producing harmful, biased, or inappropriate content.
• User trust: Establish confidence through transparent and responsible performance.
• Compliance with the Law: Comply with legal frameworks and data protection standards.
• Quality of Interaction: Optimize the user experience by ensuring clarity, consistency, and accuracy.
• Product Protection: Protect the organization's reputation by reducing risks.
• Abuse Prevention: Anticipate and prevent potentially malicious or unintended situations.

If you are planning to work with LLM Agents soon, this article is for you.