Rippling AI Agent Practices Spark Discussion on BI Paradigms
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On October 5, 2026, Shreya Shankar shared observations on the Rippling case on X: someone who hadn't used a BI tool in over five years read the case and concluded that for AI agents, choosing tools/MCPs and choosing data are becoming the same problem, and the boundary between business logic and data is getting blurrier. Rippling's data team still relies on manually reviewing agent queries and building summary tables once it spots a pattern. The observation also noted that traditional ELT is mostly push-based, while AI agents push BI toward pull: the question comes first, and the system then decides which data, transformations, and tools it needs.
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- Shreya Shankar · XRippling 案例：AI 智能体如何改变 BI 工具
一位五年多没用过 BI 工具的人看完 Rippling 案例后认为，对智能体而言，选工具/MCP 和选数据正变成同一个问题，业务逻辑与数据的边界越来越模糊。Rippling 数据团队仍靠人工检查智能体查询、发现模式后再建汇总表。传统 ELT 以推送为主，智能体让 BI 更偏向拉取：问题先到，系统再决定需要哪些数据、转换和工具。
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Current interest 3·Peak within comparable coverage 9（Oct 5, 15:00）·Change over 24 hours within comparable coverage -50%
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