Varant Zanoyan and Nikhil Simha Raprolu of Zipline AI explain why traditional feature stores are the wrong abstraction. They detail the journey of Chronon, the open-source engine born at Airbnb and battle-tested at Stripe, which focuses on compute, orchestration, and real-time correctness to solve the hardest data engineering challenges in ML, from fraud detection to powering modern AI agents with features and embeddings.
Jacqueline Cheong and Robin Tang, founders of real-time data streaming platform Artie, discuss their journey from identifying the critical need for fresh data at companies like OpenDoor to building a production-ready solution, acquiring their first major customer Substack via a cold email, and navigating the complex technical challenges of real-time data processing at scale.
David Jayatillake, VP of AI at Cube.dev, discusses the critical role of a headless, open-source semantic layer in the modern data stack. He argues against proprietary, BI-tool-specific semantic layers that create vendor lock-in and advocates for a decoupled approach. The conversation explores how AI agents can automate the entire data pipeline—from ingestion and transformation to generating and querying the semantic layer—and compares the functionalities of semantic layers and feature stores, highlighting the crucial difference of temporality.
Lior Gavish, CTO and co-founder of Monte Carlo Data, discusses the critical transition from data observability to agent observability. He covers the widespread adoption of AI agents in data teams, the new challenges they introduce for monitoring, and why traditional tools fall short in providing the necessary insights into agent performance, security, and governance.
Matthew Glickman, CEO of Genesis Computing, discusses the rise of AI data agents designed to automate complex data engineering workflows. He covers the "last 10%" problem in enterprise AI, the unique value of targeting the data engineer persona, and how these agents can tackle challenges like legacy system migration and knowledge capture, ultimately giving valuable time back to data teams.
Ciro Greco, CEO of Bauplan, outlines a new paradigm for data engineering that applies software engineering principles like version control, transactionality, and a code-first approach to build a programmable lakehouse designed for AI-driven automation and enhanced developer productivity.