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
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]
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