This article proposes a three-layer architecture for implementing guardrails in large language model (LLM) applications. The proposed framework includes layers for prompt engineering, Retrieval-Augmented Generation (RAG), and agentic control. This approach aims to enhance the safety and reliability of generative AI systems by providing structured methods for managing their outputs and behaviors. AI
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IMPACT Provides a structured framework for developers to implement safety and control mechanisms in generative AI applications.
RANK_REASON The article presents a novel architectural approach for building safety guardrails for LLM applications, akin to a research paper. [lever_c_demoted from research: ic=1 ai=1.0]
