5 Lessons From Building a Multi-Plane Network Fabric for Agentic AI
CoreWeave, Tuesday, August 25th, 2026
CoreWeave shares five lessons from building an east-west fabric for agentic inference rather than foundation model training.
CoreWeave contrasts two very different networking problems. Training a foundation model is, from the east-west fabric's point of view, well-behaved: thousands of GPUs run the same collective at roughly the same time, repeatedly, for weeks, which makes traffic predictable and tunable.
Agentic AI inference is not like that, with irregular, bursty communication patterns driven by independent requests. The post sets out five lessons from building a multi-plane network fabric designed for that second regime, covering what assumptions from training-optimized fabrics break down and how the design had to change.