Mike Freedman and Ajay Kulkarni, founders of Tiger Data, join the podcast to unveil Agentic Postgres, a database re-imagined for AI agents. 

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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

Nick Schrock, CTO of Dagster, discusses the critical role of data orchestration in the AI era, framing “context pipelines” as the new data pipelines that form the foundation of any AI strategy. He introduces Compass, a new Slack-native tool for collaborative, exploratory data analysis designed to replace the 80% of ad-hoc BI dashboards. 

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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

Ben Lorica and Evangelos Simoudis discuss AI-bubble signals (runaway revenue multiples, circular financing), why many enterprise pilots stall, and what separates leaders (use-case matrices, cross-functional ownership, hard metrics). They also examine U.S.–China tech competition in robotics and semiconductors, and offer a pragmatic view on humanoid robots — what works now versus what’s still research-grade.

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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

Luke Wroblewski of Sutter Hill Ventures joins the podcast to discuss the paradigm shift in building AI applications. He explains how the traditional model of “code + database” is being replaced by “URL + model,” where the AI agent itself becomes the application logic. 

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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

Heiko Hotz and Sokratis Kartakis of Google Cloud discuss the Agent-to-Agent (A2A) protocol, a new standard for enabling collaboration between AI agents built on different frameworks.

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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

Zhen Lu, CEO of Runpod, joins the podcast to discuss what it means to build an “AI-first” cloud, moving beyond the architectures of the Web 2.0 era. 

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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

Yoni Leitersdorf, CEO of Solid, joins the podcast to demystify why simply pointing an LLM at a database for text-to-SQL doesn’t work. He explains the critical need for a semantic layer to provide business context, turning raw data into a “Rosetta Stone” that AI can actually understand. 

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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

Ben Lorica and Evangelos Simoudis discuss some takeaways for AI practitioners from the recent AI Conference. They cover the disconnect between the hype and reality of AI agents in the enterprise, the critical importance of building reliable and trustworthy AI applications, and the potential impact of new H-1B visa policies on tech startups and innovation.

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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

Jakub Zavrel, CEO of Zeta Alpha, joins the podcast to discuss the practical evolution from traditional enterprise search to powerful “deep research” systems. 

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Detailed show notes - with links to many references - can be found on The Data Exchange web site.

Andrew Rabinovich, CTO and Head of AI at Upwork, discusses how digital work marketplaces serve as ideal testing grounds for AI agents, exploring their custom reinforcement learning approach called RLEF (Reinforcement Learning from Experience). 

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Detailed show notes - with links to many references - can be found on The Data Exchange web site.