Building for the Rising Complexity of Agentic Systems with Extreme Co-Design

Agentic AI systems fundamentally differ from chatbots by dynamically chaining tool calls, spawning sub-agents, and managing context windows — creating structurally unpredictable token consumption patterns. Analysis of a real Claude Code session shows 283 inference requests, context growing from 15K to 156K tokens, and up to 15x more token usage than standard chat. Conventional GPU infrastructure breaks under these demands due to the throughput-latency tradeoff. NVIDIA's answer is 'extreme co-design': the Vera Rubin NVL72 platform combining specialized hardware (Vera CPU, Groq 3 LPX for low-jitter generation, NVLink 6, ConnectX-9, BlueField-4) with software components (Dynamo with AFD, NVFP4, TRT-LLM WideEP, Speculative Decoding) to deliver 400+ tokens/second/user on trillion-parameter MoE models at 400K context — making agentic systems economically viable at scale.