This blog post discusses the limitations of current enterprise AI implementations which typically involve connecting large language models (LLMs) to existing data without fully utilizing the potential of data-native AI agents. The author argues for a shift towards approaches that allow AI agents to work more closely with data, highlighting how this can improve the effectiveness and efficiency of AI in enterprise settings.