Rajiv Shah

Rajiv Shah, Chief Evangelist at Contextual AI and an active content creator, shares insights from his year of building retrieval-augmented generation (RAG) pipelines. He discusses why many AI pilots fail and emphasizes the importance of evaluation and error analysis. Shah explains how RAG differs from traditional model fine-tuning and sheds light on multi-step reasoning in models. He warns against using large language models for every problem and highlights the need for user-focused AI projects that provide measurable value.