Distributed Readings

AI agent infrastructure needed to scale horizontally and support long-running interactive tasks without being constrained by stateful architecture patterns.

Real-time AI agents with long-lived stateful bidirectional streams cannot be effectively load-balanced using traditional request-response metrics because server capacity is obscured by the nature of continuous conversations.

Engineers need a systematic way to diagnose performance bottlenecks in TPU-based machine learning workloads to understand whether they are constrained by compute, memory, or network resources.