# Why the Frontier Ecosystem must be Open — Matei Zaharia and Reynold Xin, Databricks

Page: https://stenobird.com/podcast/latent-space-ai-engineer/why-the-frontier-ecosystem-must-be-open-matei-zaharia-and-reynold-xin-databricks
Text version: https://stenobird.com/podcast/latent-space-ai-engineer/why-the-frontier-ecosystem-must-be-open-matei-zaharia-and-reynold-xin-databricks.md
Podcast: [Latent Space: The AI Engineer Podcast](https://stenobird.com/podcast/latent-space-ai-engineer)
Published: 2026-06-24T18:53:16+00:00
Episode link: https://www.latent.space/p/databricks
Audio file: https://api.substack.com/feed/podcast/203293676/dd012c693ce8a0df476abdb30707f110.mp3
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Duration seconds: 4132

## Resource

We’re excited to have Databricks join us at AIEWF , among hundreds of the top companies in the AI Engineer ecosystem. LS subscribers can use their discount to get past the late bird pricing and access over $50k in sponsor offers ! Everyone is still talking about Satya’s Frontier Ecosystems post , but few have actually built a ( now $175 billion ) frontier ecosystem and cloud like our guests today. From open-sourcing the layer above coding agents to rethinking databases for the agent era, Databricks cofounders Matei Zaharia and Reynold Xin are pushing the company beyond the lakehouse into a full data-and-AI operating system. In this episode, Matei and Reynold join swyx at the 2026 Data + AI Summit to unpack Omnigent , LTAP , Lakebase , agent security , open formats, Mosaic , and why databases may matter more than ever once AI agents start doing real work. We go deep on Omnigent : Databricks’ open-source meta-harness for combining, controlling, and sharing agents across Claude Code, Codex, Cursor, Pi, custom agents, and internal tools . Matei explains why coding agents and enterprise agents run into the same problems: portability, collaboration, session history, security, spend controls, and the need for a common API above every harness. Then Reynold walks through Databricks’ database dream: why CDC is brittle enough to joke that it means “continuous data corruption,” why HTAP has been the holy grail of database engineering , and why Databricks thinks LTAP gets most of the benefits by unifying the storage layer instead of collapsing every query engine. We also cover Databricks’ infrastructure scale , the culture behind rapid prototyping , the difference between tech and enterprise customers, Databricks vs Snowflake , whether vector databases should have ever existed , th…

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