Foundation models come with broad language and reasoning capabilities across use cases and modalities based on the training datasets used. Models understand language and can follow instructions, but specialized workflows often require context that is restricted, specialized, or proprietary. Customizing an agent solves this challenge by shaping how the agent reasons under constraints, which tools it selects, how it structures its outputs, and how reliably it executes domain workflows.
Mastering Agentic Techniques: AI Agent Customization | NVIDIA Technical BlogIn practice, the most effective agent customization combines multiple techniques in sequence. The stages of a representative pipeline are outlined below. Start with system prompts, tool and skill definitions, and retrieval to establish baseline behavior.
Mastering Agentic Techniques: AI Agent Customization | NVIDIA Technical Blog…She is specialized in multimodal generative AI, large-scale model training, and inference optimization for LLMs and VLMs. She holds a PhD in Multimodal Generative AI from Université Pierre et Marie Curie…
…He manages a global team who are responsible for installations, implementations, and training sessions of cloud-native AI solutions. View all posts by Guy Saltoun View all posts by Guy Saltoun Comments
…run large-scale AI training infrastructure. If you have questions or want to share what you’re building, visit SlinkyProject on GitHub. Discuss (0) Discuss (0) Tags Data Center / Cloud | Developer Tools…
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…This AI model is trained on a character dataset built from the original photographs of the model. Using a synthetic generation pipeline, the base character dataset is expanded to variants with different…
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…She joined from Gretel, where she was the VP of marketing, and led a team promoting synthetic data generation for AI model training. Prior to this role, she served as the head…
Agentic AI / Generative AI Develop Native Multimodal Agents with Qwen3.5 VLM Using NVIDIA GPU-Accelerated Endpoints Feb 27, 2026 By Anu Srivastava Discuss (0) Discuss (0) L T F R E…