Scott Barnett et al. present ‘Seven Failure Points When Engineering a Retrieval Augmented Generation System’, a discussion of potential issues when implementing RAG with LLMs. Drawing from case studies across diverse domains (research, education, biomedical), this paper is an invaluable resource for software engineers working with semantic search and LLMs.

• Outlines seven specific failure points discovered across three domain-specific case studies.
• Offers lessons learned on RAG system design and highlights the need for operational validation and adaptable robustness.
• Suggests future research directions for the software engineering community in regards to RAG.

I believe this paper’s importance lies in its pragmatic approach to RAG system challenges, offering a clear roadmap for the AI community to overcome these hurdles. The real-world implications of this work are vast, highlighting the significance of trial and error in the evolution of more reliable AI systems. Read more