Evolving AI Agents: From Prompt Learning to Scalable Data Foundations

​An evening for AI developers to learn about Prompt Learning - a prompt optimization technique designed to help agents evolve and self-improve at a low cost. See how making prompt updates using real agent data can lead to better improvement of your agents - even compared to reinforcement learning and fine-tuning.

Overview:
Join Arize and Couchbase at Betaworks NYC for an evening of technical talks, demos, and networking with fellow AI engineers.

Discover how to improve agent performance through prompt experimentation and learn why data foundations are critical for scaling AI applications.

Enjoy food, drinks, and great conversation with the NYC AI community.

​Agenda

​5:30 PM – 6:30 PM
Check-in, networking, food & drinks

​6:30 PM – 7:00 PM
Talk: Improving Agents Through Prompt Learning
Priyan Jindal, Arize AI
Explore how prompt learning techniques and observability can help agents evolve and self-improve. See live examples of experimentation, tracing, and evaluation using real agent data.

​7:00 PM – 7:30 PM
Talk: Rethinking Data Foundations for AI Agents at Scale
Vani Jaiswal, Couchbase
Learn why NoSQL databases are the backbone of scalable AI systems. Discover how Couchbase integrates with LLMs to deliver the speed, reliability, and context awareness needed for high-performance agents—plus a live demo.

​7:30 PM – 7:40 PM
Community Demos
Showcase your projects or join to see what other developers are building.

​7:40 PM – 9:00 PM
Networking, food, and drinks