Building AI Agents That Actually Remember
Details
NOTE: REGISTER HERE
PLEASE REGISTER ON LUMA TO BE ACCEPTED.
AI agents can look great in a demo, then fall apart the moment memory, retrieval, and real-world complexity matter.
This meetup is about what it actually takes to build agent systems that can remember the right things, retrieve the right context, and behave more reliably in production.
We'll hear from speakers at Google, Tavily, and Oracle, each sharing practical lessons from building real AI systems, followed by audience Q&A and time to meet others working in the space.
This is a relaxed, down-to-earth local chapter meetup designed for learning, good conversations, and connecting with other engineers and builders in NYC.
TOPICS WE'LL EXPLORE
Some of the themes across the evening will include:
- Agent memory and long-term context
- Retrieval and knowledge systems
- Databases and infrastructure for AI agents
- Building agent systems that are more reliable in production
- The difference between demo-quality agents and production-ready systems
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## AGENDA
5:30 - 6:15 PM | Arrival & Networking
Check-in, food, drinks, and informal networking
6:15 - 6:30 PM | Welcome & Kickoff
Opening remarks from the MLOps Community team and Oracle
6:30 - 7:00 PM | Pier Paolo Ippolito - Google
7:00 - 7:30 PM | Dean Sacoransky - Tavily
7:30 - 8:00 PM | Richmond Alake - Oracle
8:00 – 8:30 PM | George Pearse - Visia
8:30 – 9:30 PM | Open Q&A + Networking
Audience questions, breakout chats, drinks, and networking
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## WHO SHOULD ATTEND
Engineers, ML practitioners, and technical builders interested in AI agents, retrieval systems, memory architectures, and real-world LLM infrastructure.
PLEASE REGISTER ON LUMA
https://luma.com/uk9vvgal
https://luma.com/uk9vvgal
https://luma.com/uk9vvgal