Core Viewpoint - The article discusses the transformative impact of Agentic AI on the software ecosystem, particularly how traditional data warehouses are being challenged by new architectures that prioritize semantic and responsive data handling over structured querying [1][3][34]. Group 1: Industry Changes - Snowflake's recent CEO change signals a paradigm shift in the data warehouse landscape, moving from a focus on traditional data warehousing to an AI-first approach [2][3]. - The emergence of Agentic AI, which acts as an intelligent agent capable of understanding and executing tasks, raises questions about the relevance of traditional decision support systems designed for human users [4][5][22]. - The traditional data warehouse, once a critical asset for enterprises, may become merely a repository of raw data for these intelligent agents, diminishing its value [6][30]. Group 2: Evolution of Data Architecture - The evolution of data warehouse architecture has seen significant milestones, from Bill Inmon's foundational concepts in the 1970s to the rise of cloud-native solutions like Snowflake in 2015 [9][18]. - The article outlines how the introduction of big data technologies and cloud computing has reshaped the data landscape, leading to a decline in the dominance of traditional MPP architectures [16][17]. - The concept of Agentic Data Stack is introduced as a new architecture that integrates data and semantics, designed to meet the needs of AI agents [36][39]. Group 3: Future Implications - The future of data warehouses will likely involve a shift from human-centric designs to architectures that cater to AI agents, fundamentally altering how data is stored, processed, and utilized [30][31]. - The article predicts that as Agentic AI becomes more prevalent, the roles of various business functions will be redefined, with agents taking over tasks traditionally performed by humans [25][27]. - The transition to Agentic Data Stack is expected to reduce the construction cycle of data warehouses significantly, enabling real-time data access and processing capabilities [39][40].