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Building an Advanced AI Skill Security Auditing Pipeline with NVIDIA SkillSpector, LangGraph, YARA Rules, SARIF, and CI Policy Gates

In this tutorial, we build a workflow for evaluating the security posture of AI skills with NVIDIA SkillSpector. We create a synthetic skill marketplace containing clean, risky, malicious, and MCP-based examples, then scan each skill through SkillSpector’s LangGraph inspection pipeline. We examine risk scores, categorized findings, confidence levels, analyzer completeness, and executable-script indicators before organizing

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Hybrid AI Assistant Architecture: When to Use NLU, RAG, Deterministic Flows, and LLMs

TL;DR Enterprise assistants should not send every request directly to an LLM. A production-ready assistant needs a routing architecture that selects the right pattern for the job: deterministic flows for controlled tasks, NLU for intent routing, RAG for grounded knowledge answers, LLMs for synthesis and flexible language, and human handoff for ambiguity, risk, or exception

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