Beyond Naive RAG: Why Retrieval Is Not Memory
from Frontier AI Architect Hosted by Amar
Legal research tools built on retrieval and on some of the best document collections in any industry still hallucinated on 17% to 33% of test queries. This episode explains where retrieval breaks and what a production agent needs on top of it. In this episode: - What the Stanford and Yale study of AI legal research tools found - Why similarity search fails on multi-document and corpus-wide questions - Three layers: better retrieval, graph structure and agent memory, with the cost of each - What the GraphRAG evidence shows, and what an independent benchmark added - The case that long context windows make most of this unnecessary Read the full article with all sources: https://substack.com/@frontieraiarchitect/note/p-221333964?r=978zej Frontier AI Architect is written by David Amar. LinkedIn: https://www.linkedin.com/in/david-amar-575192441 Newsletter: https://frontieraiarchitect.substack.com Contact: [email protected] This episode's audio is AI-generated, based on an article written by David Amar.
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