NVIDIA Tutorial: Tune Agent Frameworks Before Fine-Tuning Models
NVIDIA Developer · youtube · 2026-07-14
This official NVIDIA livestream tutorial, featuring the LangChain team, highlights a core philosophy: When AI Agents fail, avoid immediately fine-tuning the model. Instead, prioritize troubleshooting and optimizing the execution framework surrounding the model.
Through a practical demonstration, the tutorial shows how to systematically debug Agents using LangChain Deep Agents and the NVIDIA Nemotron 3 Ultra model:
- Run Evaluations: Benchmark the model using LangChain Deep Agents' evaluation tools and analyze failure logs.
- Fix the Framework: Address specific failure points by writing and registering framework patches via middleware, prompt modifications, or tool description updates.
- Validate Results: Verify the fix's effectiveness on a held-out test set to prevent overfitting on the evaluation data.
- Environment Deployment: Demonstrates how to run the Agent within NVIDIA OpenShell using the NemoClaw blueprint.
More from coding & agent
- Dev builds interactive 3D product experience with GPT-6 Astra + Hyper3D Rodin — nikola_mr64990 · 2026-09-11
- Codex tip: use Sol with Astra and Luna sub-agents to save usage — pvncher · 2026-09-11
- agents-best-practices: a provider-neutral Agent Skill for designing and auditing agentic harnesses — tom_doerr · 2026-09-11
- Cognition's SWE-2 uses a KKT duality argument in RL to shift the effort Pareto curve — YouJiacheng · 2026-09-11
- First-ever Three.js Conference lands in Paris, with a panel on AI-shortened design workflows — OdinLovis · 2026-09-11
- Data engineering, not agent frameworks, is the real bottleneck for enterprise AI agents — dhruv2038 · 2026-09-11