Put Humans in Command of Agent Fleets

At NVIDIA GTC 2026, Jensen Huang spent three hours in front of 30,000 attendees from 190 countries making a single argument: the era of agentic AI is no longer a forecast — it's the operating reality of every serious technology company on the planet.

Huang traced the arc clearly: "In 2023, it was ChatGPT. In 2024, it was reasoning models like o1. In 2025, it was huge models with massive context windows like Claude Code." He called Claude Code the first "agentic model" — software that doesn't just answer questions but reads files, writes code, compiles, tests, and iterates autonomously. He noted that 100% of NVIDIA is using agentic tools every day.

The shift Huang described is fundamental: "For the first time, you don't ask the AI what, where, when, how. You ask it create, do, build. AI now has to think. In order to think, it has to inference." These are no longer prompt-and-response tools. They are autonomous systems that reason, plan, call tools, spawn sub-agents, and operate over long horizons.

NVIDIA projects at least $1 trillion in infrastructure demand through 2027 to power this shift. Huang predicted that every engineer will receive an annual "token budget" alongside their salary — computational fuel to amplify their output 10x through agentic collaboration. Every SaaS company, he said, will become an "Agentic as a Service" company.

Agents are writing production code, making tool calls, modifying live infrastructure, and spawning sub-agents to divide work. The complexity is compounding fast. Jensen Huang described OpenClaw at GTC as "the operating system of agentic computers" and compared its significance to Windows and Linux. NVIDIA announced NemoClaw to make autonomous agents safe for enterprise deployment.

But the human side of this equation is underserved. Agents run in terminals. Their reasoning is hidden behind scrollback. When five agents work in parallel, there's no unified view. When one regresses, you find out after the damage is done.

AgentMux is the missing layer — the observability and orchestration surface that sits between you and your agents. It keeps their reasoning, panes, and messages in one view, and gives agents themselves a first-class API to act inside it. Built for the workflows emerging right now, and designed to evolve as fast as the field itself.

Huang told 30,000 developers that every company will need an agentic strategy. That every engineer will have a token budget. That the inference inflection point has arrived and the demand curve is exponential.

We agree. And we believe the tooling for this era should be fast, open, and relentlessly focused on the human operator. Not another Electron shell consuming half a gigabyte of RAM. Not a SaaS dashboard that proxies your agent traffic through someone else's servers. A native, open-source desktop app with a Rust core that runs locally, keeps your data on your machine, and puts you in command of the agents doing your work.

That's AgentMux. That's the vision.