AI Engineer · July 23, 2026

Learned Execution Graphs for Anomaly Detection & Drift in APIs — Ritvik Pandya, JP Morgan Chase

Learned Execution Graphs for Anomaly Detection & Drift in APIs — Ritvik Pandya, JP Morgan Chase video thumbnail
Why it matters

Traditional monitoring reported the system healthy: latency down, errors at zero. A mandatory processing step had been silently skipped, and nothing caught it except the graph.

My takeaway: Learned Execution Graphs for Anomaly Detection & Drift in APIs — Ritvik Pandya, JP Morgan Chase is a model-evaluation signal. The practical read is to tie capability claims to evidence, launch criteria, and regression tests rather than relying on demos or benchmark headlines.