Agentic AI is changing how enterprises design and operate networks. In this episode of the AI in Networking showcase, Kishan Ramaswamy (Director, Product Management, Arista) explains why interactive, AI-driven experiences demand low latency, symmetric bandwidth, and deterministic performance—and how Arista’s cloud-grade fabric, visibility, and segmentation help AI agents perform reliably and securely.
Brendan Gibbs, Vice President, AI Routing & Switching Platforms (5:02–5:36), discusses bringing cross-domain outcomes to AI networking.
What you’ll learn
• Why AI apps already dominate enterprise/branch traffic
• The networking properties that matter for AI agents (latency, symmetry, predictability, security)
• How Arista’s approach (fabric + telemetry + policy) supports AI at scale
• Where AI networking is heading next
⏱️ Timestamps / Chapters
00:00 – AI at the edge: Proliferation of enterprise AI apps; bandwidth realities
00:26 – Experience expectations: Interactive AI needs instant responses
01:12 – Networking properties for AI: Throughput vs. determinism; symmetric bandwidth
01:38 – Symmetry matters: Matching request/response flows for AI interactions
02:01 – From theory to enterprise: Translating AI app behavior to real networks
02:23 – Predictability & performance: Designing for interactive AI traffic
02:44 – Adoption trends: More AI use cases across branches and sites
03:04 – Cloud AI vs. enterprise AI: Which use cases fit where
03:30 – Resiliency example: What happens when a link goes down
03:55 – Ops impact: Time, workflows, and why telemetry/policy are key
04:16 – Policy & segmentation: Enforcing app-aware controls for AI traffic
04:41 – Identifying AI apps by behavior: Classify → apply right tech/policy
05:02 – Guest: Brandon Gibbs (VP, AI Routing & Switching Platforms) — cross-domain, actionable outcomes (to ~05:36)
05:37 – Beyond GenAI: Multi-domain correlation for faster root cause
06:14 – Closing: What’s next as AI platforms integrate across domains
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