Guardrails in Agentic AI are rules, constraints & control mechanisms that ensure an AI agent behaves safely, reliably, and within intended boundaries - especially when it is making decisions, taking actions, or interacting with external systems. Think of Guardrails like "Safety + Governance + Control" layer around Agentic AI agent. Why Guardrails are critical in Agentic AI ? Unlike simple LLM prompts, agentic systems: Take autonomous actions(APIs, DB updates, workflows) Use tools and external systems Maintain memory and context over time Without Guardrails, they can: Hallucinate and take wrong decisions Trigger unintended workflows(Ex: Deleting entire data!) Leak sensitive information Spiral into infinite loops or bad reasoning Guardrails are categorized into 3 types: RAG Guardrails MCP Guardrails Agentic AI Guardrails Lets discuss one by one. RAG Guardrails 1) Input Guardrails Length Check User provided 3000 page document, asked to summarize this document System may cr...