2026 Talks
The Modern Data Stack Lost the War: Stop Building more DataFrame APIs
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- Lightning Talks
After more than a decade of limited innovation, the modern data stack is still slow, fragmented, and painfully repetitive. Every new dataframe library promises better ergonomics or performance, yet converges on the same API with the same limitations. The failure isn’t execution or scale, it is ignoring that appearance doesn't matter anymore: Agents and AI-first developers couldn't care less about how an API looks today. In this talk we’ll examine why the dataframe paradigm keeps reproducing itself, why it consistently underdelivers, and why the data stack’s biggest problems were never going to be solved at the API layer first. Princess Leia once put her trust into Obi-Wan Kenobi - what if we did the same with simple Python functions? Could we defeat the evil empire of DataFrame APIs?
Member of Technical Staff
Leonhard Spiegelberg
OpenAI
Leonhard Spiegelberg is a Member of Technical Staff at OpenAI, where he works on exabyte-scale data and agentic infrastructure for production-critical workloads. He holds a PhD in Computer Science from Brown University as a Facebook Fellow, where he researched speculative compilation techniques for efficient data processing. Previously at Snowflake, he originated and shipped pandas on Snowflake, bringing native DataFrame computing to the data warehouse. In addition to multiple patents, his research has been published at VLDB, SIGMOD, and OSDI.
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