Guardrails AI Tutorial: Validators, Guards & on_fail Explained | AI Security Full Course EP-6

Writing guardrails by hand works. But real AI teams often use a framework. 🛡️ In this video we move from hand-written guardrails to guardrail frameworks. We compare the two most popular ones, Guardrails AI and NeMo Guardrails, and then learn Guardrails AI step by step by building our own custom validator in Python. 🛡️ You'll learn: • Why teams use a guardrail framework instead of custom code • Guardrails AI vs NeMo Guardrails: style, strengths and when to use which • The 3 core concepts: Validator, Guard and on_fail • All on_fail actions explained, and 4 of them (EXCEPTION, FIX, NOOP, REFRAIN) tested live on the same validator • How to build a custom validator with @register_validator that masks phone numbers 🧰 Tech stack: Python, Guardrails AI, Jupyter Notebook ⏱️ Chapters: 00:00 Part 1 00:54 Part 2 07:09 Part 3 13:14 Part 4 17:15 Part 5 20:15 Part 6 27:27 Part 7 29:25 Part 8 31:37 Part 9 👉 Next video: we build a secure chatbot with Guardrails AI, with an input guard, an output guard and defense in depth. 👩‍💻 Perfect for: AI/ML engineers, Python developers, and anyone preparing for AI engineer or AI security interviews. 💻 Free code (GitHub): https://github.com/dearnidhi/ai-secur... ⭐ If it helps you, please star the repo! 📺 Full playlist:    • AI Security Full Course | LLM Security, Pr...   #GuardrailsAI #AIGuardrails #AISecurity #LLMSecurity #Python #NeMoGuardrails #GenerativeAI #ResponsibleAI #CyberSecurity #ArtificialIntelligence #MachineLearning #LLM