RAG 的概念很糟糕，让大家忽略了应用构建中最关键的问题

Core Viewpoint - The article emphasizes the importance of Context Engineering in AI development, criticizing the current trend of RAG (Retrieval-Augmented Generation) as a misleading concept that oversimplifies complex processes [5][6][7]. Group 1: Context Engineering - Context Engineering is considered crucial for AI startups, as it focuses on effectively managing the information within the context window during model generation [4][9]. - The concept of Context Rot, where the model's performance deteriorates with an increasing number of tokens, highlights the need for better context management [8][12]. - Effective Context Engineering involves two loops: an internal loop for selecting relevant content for the current context and an external loop for learning to improve information selection over time [7][9]. Group 2: Critique of RAG - RAG is described as a confusing amalgamation of retrieval, generation, and combination, which leads to misunderstandings in the AI community [5][6]. - The article argues that RAG has been misrepresented in the market as merely using embeddings for vector searches, which is seen as a shallow interpretation [5][7]. - The author expresses a strong aversion to the term RAG, suggesting that it detracts from more meaningful discussions about AI development [6][7]. Group 3: Future Directions in AI - Two promising directions for future AI systems are continuous retrieval and remaining within the embedding space, which could enhance performance and efficiency [47][48]. - The potential for models to learn to retrieve information dynamically during generation is highlighted as an exciting area of research [41][42]. - The article suggests that the evolution of retrieval systems may lead to a more integrated approach, where models can generate and retrieve information simultaneously [41][48]. Group 4: Chroma's Role - Chroma is positioned as a leading open-source vector database aimed at facilitating the development of AI applications by providing a robust search infrastructure [70][72]. - The company emphasizes the importance of developer experience, aiming for a seamless integration process that allows users to quickly deploy and utilize the database [78][82]. - Chroma's architecture is designed to be modern and efficient, utilizing distributed systems and a serverless model to optimize performance and cost [75][86].