# Develop Lightweight USD Runtimes Faster with AI Agents

[NVIDIA Developer Blog](https://yomu.fyi/company/nvidia-developer-blog) · Michelle Horton · Jul 15, 2026

**Type:** Explainer

## Summary

Building custom Universal Scene Description (USD) implementations traditionally required adapting large existing codebases to meet specific memory footprints, application binary interfaces (ABIs), or performance requirements. The nanousd-labs project introduces an alternative approach by using AI agents to generate lightweight USD runtimes directly from the Alliance for OpenUSD machine-readable USD Core Specification. Agents parse the specification section by section, write conforming code, and validate output against specification-derived tests under engineer guidance. Written in C++ with a public C API, nanousd functions as an independent data layer that handles parsing, composition, queries, and writing without rendering pixels. This methodology enables developers to regenerate runtimes for varying deployment constraints while maintaining standard compliance through reusable workflows and skill graphs.

## Context

Building a USD implementation traditionally required adapting a large codebase, which posed challenges for physical AI teams needing specific memory footprints, ABIs, or performance characteristics.

## Approach / What changed

Directing AI agents to read the USD Core Specification as a contract, generate runtime code section by section, and iterate against a specification-derived test suite, while human engineers handle architectural decisions and performance trade-offs.

## Takeaways

- nanousd is a C++ runtime data layer with a stable public C API that parses, composes, queries, and writes USD scenes without handling rendering.
- AI agents generate code for parsing, composition, and value resolution against the USD Core Specification, while engineers oversee architecture and performance.
- Human directions for spec-compliant generation can be captured into reusable skill graphs containing structured recipes, prompts, and tests.

**Tags:** [Architecture](https://yomu.fyi/topic/architecture), [LLMs](https://yomu.fyi/topic/llm), [Open Source](https://yomu.fyi/topic/open-source)

[Read original post](https://developer.nvidia.com/blog/develop-lightweight-usd-runtimes-faster-with-ai-agents)