Nvidia just showed that the harness, not the AI model, is now the real hero
Nvidia research shows that AI agents can perform well, and not go off the deep end, through fine-tuning, even if the AI model isn't that great at the task.
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Will Nvidia publish a follow-up paper or blog post expanding on its AI agent fine-tuning findings by September 30 2026?
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Nvidia published research showing that the software scaffolding around an AI model, called a harness, matters more than the model itself when asking AI to complete long-horizon tasks that require stringing many decisions together over time. In their tests, Claude Opus 5 scored 30 percent on an interactive reasoning benchmark without a custom harness but achieved a 100 percent score when given a harness that included a supervising agent component to redirect the model when it gets stuck. This finding aligns with earlier research from other companies indicating that harness choice significantly impacts both AI performance and costs, meaning that control over the tools and rules surrounding a model can be more important than simply selecting a more advanced model. The research supports the argument for open harnesses that give users greater control over how AI systems operate.
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