Change data capture

AI Cut Our Research Time From 7 Days to 15 Minutes — Gareth Yoder, Vanguard

AI Cut Our Research Time From 7 Days to 15 Minutes — Gareth Yoder, Vanguard

Gareth Yoder of Vanguard describes modernizing a cash ledger handling up to 30 million calls per day by running data, producer, and consumer migrations in parallel. Key themes include exposing legacy code to AI through an MCP server, reducing a seven-day research cycle to fifteen minutes, reimagining rather than lifting and shifting, and maintaining observability throughout the migration.

Let's integrate AI Agents in Event-Sourced Systems — Divakar Kumar, FlyersSoft

Let's integrate AI Agents in Event-Sourced Systems — Divakar Kumar, FlyersSoft

This presentation explores integrating AI agents into existing event-sourced architectures to resolve ambiguous cases in real-time fraud detection. By leveraging a semantic layer built from various bounded contexts (transaction, device, account), specialized agents like Risk Analyzer and Behavior Analyzer use tools and short-term memory to reach a verdict, addressing the "gray zone" where traditional rule-based and ML systems fall short. The approach emphasizes layering agents without replacing existing infrastructure, enhancing judgment in production systems.

Artie: Real Time Data Streaming For The AI Age

Artie: Real Time Data Streaming For The AI Age

Jacqueline Cheong and Robin Tang, founders of real-time data streaming platform Artie, discuss their journey from identifying the critical need for fresh data at companies like OpenDoor to building a production-ready solution, acquiring their first major customer Substack via a cold email, and navigating the complex technical challenges of real-time data processing at scale.