Nvidia's Vision for Agentic AI: The "Harness" Model Beyond OpenClaw

Nvidia has surprised some observers by publicly supporting OpenClaw, the controversial agentic AI framework that became a cultural phenomenon in the developer world. To understand Nvidia's thinking, The New Stack spoke with Nader Khalil, the company's Director of Developer Technologies (and co-founder of Brev.dev, which Nvidia acquired two years ago).

How Nvidia Defines an Agent#

Khalil's framework is deceptively simple: "An agent is an LLM and a harness." The harness—the execution layer—matters as much as the model itself. He traces the evolution from ChatGPT's innovations (system prompts, multimodal inputs, memory) through tools like Cursor and Claude. "Everything here is the harness," he explains.

The key insight is that each iteration should move closer to a goal, leveraging results from prior LLM calls rather than repeating identical operations.

Why Nvidia Backs OpenClaw#

OpenClaw's explosive growth (achieving more GitHub stars than Linux in months) created bottlenecks—over 800,000 lines of code, thousands of unresolved pull requests, and a project creator dealing with scaling challenges. Rather than distance itself, Nvidia rolled up its sleeves.

"We have a couple of developers at the company that contribute to OpenClaw full time," Khalil says. He frames the relationship pragmatically: "We saw Peter [Steinberger] tweeting about some of the issues they had, and we just rolled up our sleeves and were eager to help."

The Blueprint Strategy#

Nvidia is hedging with "blueprints"—reference implementations for deploying agents safely in enterprise settings. NemoClaw (Nvidia's own agent framework) and blueprints for both OpenClaw and Hermes give enterprises proven patterns without betting everything on one framework.

Security remains a concern. Khalil notes companies need specialized runtime controls—"You have to give [agents] access to your terminal." Nvidia's OpenShell project aims to provide that security layer for teams building custom agents.

The Microwave Analogy#

The company isn't trying to be a one-size-fits-all platform. Khalil's microwave metaphor is apt: enterprises will build specialized agents tailored to their workflows, just as home cooks know their own appliance. Nvidia is partnering with CrowdStrike, Cadence, and Palantir to help teams adopt agents where they already operate.