Originally published at: Create a LangChain Deep Agents Harness Profile for NVIDIA Nemotron 3 Ultra to Improve Performance | NVIDIA Technical Blog
Agentic systems often face a trade-off between accuracy and cost. The highest-performing proprietary frontier models and harnesses provide top accuracy but are expensive. Fine-tuning offers one way to address this problem. Smaller or more efficient open models starting with lower accuracy are taught to perform better with specific agents. However, fine-tuning requires expertise and hardware…
The automation loop described here feels like the next logical step in MLOps for agents. By treating the harness profile as code and the evaluation suite as a CI/CD pipeline, we’re essentially applying software engineering rigor to non-deterministic systems. Looking forward to seeing if this pattern can be extended to multi-agent environments where the interaction between harnesses becomes even more complex. Has anyone attempted to scale this loop to multi-agent coordination yet?