# Validate AI Factory Changes with Digital Twins and AI Agents

DevFeed: [Validate AI Factory Changes with Digital Twins and AI Agents](<https://devfeed.tech/articles/validate-ai-factory-changes-with-digital-twins-and-ai-agents-66969.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/validate-ai-factory-changes-with-digital-twins-and-ai-agents/>)

Author: Avi Alkobi

Published: 2026-10-07T16:00:00Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [AI Infrastructure](<https://devfeed.tech/topics/ai-infrastructure.md>), [CI/CD](<https://devfeed.tech/topics/cicd.md>), [agentic workflows](<https://devfeed.tech/topics/agentic-workflows.md>), [Spec Driven Development](<https://devfeed.tech/topics/spec-driven-development.md>), [NemoClaw](<https://devfeed.tech/topics/nemoclaw.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [ci-cd](<https://devfeed.tech/tags/ci-cd.md>), [data-center-cloud](<https://devfeed.tech/tags/data-center-cloud.md>), [digital-twins](<https://devfeed.tech/tags/digital-twins.md>), [dsx](<https://devfeed.tech/tags/dsx.md>), [gpus](<https://devfeed.tech/tags/gpus.md>), [nemoclaw](<https://devfeed.tech/tags/nemoclaw.md>), [networking-communications](<https://devfeed.tech/tags/networking-communications.md>), [orchestration](<https://devfeed.tech/tags/orchestration.md>), [retrieval-augmented-generation-rag](<https://devfeed.tech/tags/retrieval-augmented-generation-rag.md>), [simulation-modeling-design](<https://devfeed.tech/tags/simulation-modeling-design.md>)

## AI overview

The article describes using a node-based digital twin to validate AI-factory infrastructure, software, and policy changes before production. Integrated with CI/CD, the twin gives teams a representative environment for testing configurations and workflows, while AI agents can run checks, gather operational context, and produce evidence-backed recommendations under human approval and policy controls. It highlights NVIDIA DSX Air and Brev, including a video-search workflow, as examples of applying this approach across planning, deployment, and operations.

## Source excerpt

AI factories are some of the most complex operations in the world, combining GPUs, CPUs, switches, DPUs, and SuperNICs alongside schedulers, orchestration...