Six Agent Harness Capabilities for Higher Model Performance
NVIDIA, Monday, July 27th, 2026
NVIDIA argues the agent harness, not the model, often determines end-to-end performance.
Building a capable AI agent is not primarily about choosing the right model, NVIDIA argues, because the harness surrounding the model determines how much of its capability is actually realized.
The harness covers how context is rendered, how tools are executed, how errors are surfaced, and how state persists across turns. The post sets out six harness capabilities that measurably improve performance with the same underlying model.
It gives concrete implementation guidance for each. The piece is aimed at engineers whose agent performance has plateaued despite model upgrades.