#17 Guardrails for RAG & Agentic AI Systems | Guardrails, PII & Injection Attacks | Sandboxing

Описание: 🔐 Guardrails & Safety for LLMs (PII, Prompt Injection & Sandboxing)

LLMs are powerful—but unsafe by default.

In this video, we break down guardrails and safety mechanisms required to run LLMs, RAG pipelines, and Agentic AI systems securely in production. You’ll learn how teams prevent PII leaks, defend against prompt injection attacks, and safely execute tools using sandboxing.

If you’re deploying chatbots, copilots, or autonomous agents, this video shows how to protect users, data, and systems.

🚀 What You’ll Learn

✅ What LLM Guardrails are and why they matter
✅ How PII detection, masking & redaction works
✅ Types of Prompt Injection attacks (direct & indirect)
✅ How to secure RAG pipelines from injection
✅ Sandboxing tools & code execution safely
✅ Input, output & runtime validation strategies
✅ Defense-in-depth architecture for LLM systems
✅ Real-world LLM security failures & fixes

🧠 Topics Covered

PII Handling & Data Privacy
Prompt Injection & Jailbreaks
Indirect Injection via Documents
Tool Access Control
Sandboxed Execution Environments
Policy Enforcement & Safety Filters
Secure Agentic Workflows

🏗️ Real-World Use Cases

Enterprise Chatbots
RAG-based Knowledge Assistants
Autonomous Agents & Tool Use
Customer Support AI
Internal Copilots Handling Sensitive Data

👨‍💻 Who This Video Is For

AI / ML Engineers
Backend Engineers
Security Engineers
Platform & MLOps Teams
Anyone deploying LLMs in production

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#Sandboxing #RAG #AgenticAI #AIInProduction #MLOps
#SecureAI #LLMAgents