
The episode discusses how AI agents can transform data engineering by focusing on business outcomes rather than just tools.
For years, data engineering has been about building pipelines, warehouses, dashboards, and choosing the right tools. But what if we've been solving the wrong problem? I recently sat down with Sai Sundar from WALT, who has spent decades building data platforms at Apple, Yahoo, LinkedIn, Chime, and GEICO. One idea from our conversation really stood out. Companies don't need more data tools. They need better business outcomes.Sai explained how data teams often work in silos. Engineers build pipelines. Business teams ask questions. Analysts sit in the middle translating requirements. The result is slow decisions, duplicated work, and endless back-and-forth.The next evolution isn't another platform.It's creating systems that understand business goals, work with your existing data stack, and help organizations make trusted decisions faster.Some of the topics we covered:* Why data has historically been treated as a second-class citizen* Why business outcomes matter more than adopting the latest technology* How AI is changing the role of data engineering* Why trust and transparency are becoming essential in enterprise AI* What the future of conversational data engineering could look…
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