"As with any other type of software, AI agents are vulnerable to various types of threats. Without proper safeguards, they can produce inaccurate, biased, or even harmful outputs - or take unintended actions that compromise data integrity, privacy, or user trust. To prevent AI agents from behaving in undesirable ways, AI workflow creators must establish clear guardrails that define the system's boundaries. In this article, I will provide a quick introduction to this topic."
"Without guardrails, the AI agent will likely follow the command that the user provided and issue the refund. But when we have guardrails in place, the system validates the user command and classifies it as safe/not safe. Only safe instructions have a green light for processing. If instruction is not safe, the AI agent will simply say something like " Sorry, I cannot do it. ""
Guardrails are rules, constraints, and protective mechanisms that ensure AI agents behave safely, ethically, and predictably within their intended scope. They prevent inaccurate, unwanted, or harmful outputs and block actions that exceed authority. Workflow creators must validate and classify user instructions, allowing only safe commands to execute. A practical example is a customer support agent that denies unauthorized refund requests. Guardrails can be implemented at multiple levels, including prompt-level rules embedded in system prompts or configuration, defining scope, tone, persona, and explicit boundaries for agent behavior.
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