SurrealDB New York

**Please note: to attend this event, you must be registered and approved here: https://luma.com/pt8n7cwe.
Anyone who is not registered and approved will not be admitted to the venue. Thank you.

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We’ve all done a lot of talking in the last few months (years??) about coding agents, advancements in models, and AI slop. In this meetup, we're bringing all of this together as our speakers talk about how to squeeze even more out of AI so you can actually ship something you're proud of.

Be our guest, hear from the speakers we've assembled, and bring your hard questions. We're here to learn from each other, successes and failures alike.

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​Talks
​Tobie Morgan Hitchcock (CEO, SurrealDB)
Building agent memory with knowledge graphs
​Richard Feldman (Zed, AI team)
Exploring live AI workflows + Q&A
​Shashank Goyal (OpenRouter, Founding Engineer)
Models, benchmarks, and how everything really stacks up

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​Agenda

• ​18:00 - Doors + drinks + food
• ​18:30 - Welcome
• ​18:35 - Lightning talks (15 minutes each)
• ​20:20 - Drinks + networking
• ​21:00 - Close

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​About the speakers
​Tobie Morgan Hitchcock (CEO, SurrealDB)
​Tobie Morgan Hitchcock is CEO & Co-Founder of SurrealDB, an AI-native, multi-model database for modern applications. A tech entrepreneur and software engineer with 17 years in software and cloud computing, he specialises in distributed databases and highly available systems.

​Richard Feldman (Zed, AI team)
​Richard created the Roc programming language, wrote the book Elm in Action, and hosts the Software Unscripted podcast. And now he's building Zed's AI features and shipping (seemingly) faster than the speed of light.

​Shashank Goyal (OpenRouter, Founding Engineer)
​Shashank is a seasoned software engineer and founder, currently working on making AI inference easier for millions of devs at OpenRouter.

## Please note - to reserve a spot for this webinar you must register at: https://sdb.li/4tIXaBo

Architecting Agentic Data Planes: Lessons from OpenAI’s Billion Dollar Postgres Mistake

OpenAI’s PostgreSQL scaling story is impressive engineering. It’s also a cautionary tale.

Agentic AI systems introduce high write concurrency, bursty traffic patterns, and blended transactional + retrieval workloads. Traditional database architectures weren’t designed for this shape.

In this live webinar, we'll break down:

• The architectural constraints that surface at scale
• The operational cost of “just making it work”
• Why AI workloads magnify single-writer bottlenecks
• What a natively distributed, horizontally scalable data plane looks like
• How to serve transactional and AI workloads from one live dataset - without duct tape

​Speaker

Matthew Penaroza
Head of Solution Architecture, SurrealDB
​Matthew Penaroza is Head of Solution Architecture at SurrealDB, where he helps design and scale distributed AI systems for global enterprises. As the solutions architect behind the core database systems at companies such as Plaid, Uber, and Atlassian, he brings firsthand insight into how the world’s largest organizations design data infrastructure and how those same architectural principles can be applied to AI systems that demand context precision and intelligent data management.