Rippling case study: agents turn BI from push-based ELT into pull-based analytics
sh_reya · x · 2026-10-05
Reacting to Rippling's AI×GTM video, shreya shares observations: for agents, choosing a tool/MCP and choosing what data to retrieve converge into the same problem — both are context assembly, blurring the business-logic/data boundary. BI shifts from push-based (humans pre-build tables/dashboards) to pull-based (question arrives first, system figures out retrieval). Notably, Rippling's data team still manually inspects agent queries and creates new rollup tables when patterns emerge — materialized-view fans would love this. A hands-on case for agent data stacks.
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