Building the Context Flywheel for AI Data Agents
About this episode
Prukalpa Sankar discusses building a context flywheel for AI agents in data-intensive organizations.
Summary In this episode Prukalpa Sankar, co-founder of Atlan, talks about what it takes to build a “context flywheel” for AI agents in data-intensive organizations. She explained why model intelligence alone isn’t enough to make AI useful in production, and how real performance depends on contextual intelligence: institutional knowledge, semantic meaning, procedural know-how, and access to the right tools. She also dug into how metadata catalogs are evolving into broader context layers that serve both humans and agents, and why agentic systems are changing the economics of metadata and governance work. Prakulpa shared Atlan’s perspective on bootstrapping context from existing systems such as warehouses, BI tools, query logs, and SaaS applications, then using simulation, traces, and human governance loops to improve agent accuracy over time. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Your host is Tobias Macey and today I'm interviewing Prukalpa Sankar about strategies for building a context flywheel for your data agents Interview Introduction How did you get involved in the area of data management? You…
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