Generalists Can Also Dig Deep

An interview with AI builder Ida Silfverskiöld explores the value of a generalist background in developing AI products, combining technical, product, and market perspectives. The discussion covers the practical application of AI agents, noting they often overcomplicate systems where simpler Retrieval-Augmented Generation (RAG) patterns would suffice. Key challenges in building RAG systems are highlighted, specifically the difficulty in optimizing document chunking and retrieval to provide sufficient context without irrelevant information. The conversation also touches on the necessity of custom evaluations for AI systems, with metrics tailored to specific use cases like coding assistants or e-commerce agents.