Developing NVIDIA Holoscan Applications with CLI, Skills, and AI Coding Agents

Agent-Driven Development on NVIDIA's Edge Platform

NVIDIA researchers have detailed a workflow for building edge AI applications by guiding a general-purpose AI coding agent with platform-specific tools. This work, centered on the NVIDIA Holoscan platform, illustrates how structured interaction through a command-line interface (CLI) and predefined 'skills' can accelerate the development of complex, real-time systems like medical imaging analysis, moving beyond simple code completion tasks.

The process involved an engineer setting high-level goals for building an endoscopic tool segmentation application. The agent, identified as Codex with GPT-5.6, then used the Holoscan CLI, HoloHub code repository, and documentation to iteratively implement features. Over three iterations, the agent scaffolded a new application, introduced repeatable benchmarking modes, and subsequently optimized the data pipeline to improve performance, all based on concise engineer prompts.

Performance Gains and Workflow Efficiency

An ablation study conducted as part of the research underscored the importance of a well-designed development environment for these workflows. Providing the AI coding agent with the full combination of the CLI, curated skills, and documentation yielded the most efficient outcome. This approach suggests that the future of AI-assisted development for specialized fields depends on creating platforms explicitly designed for human-agent collaboration, where agents can leverage structured tools rather than just parsing unstructured documentation. The optimization iteration yielded significant performance improvements:

• Rendered throughput: 306.9 FPS (a 50.5% increase)
• Mean application-path latency: 3.247 ms (a 33.6% reduction)
• P95 application-path latency: 4.554 ms (a 27.4% reduction)

The research highlights that the true value of AI coding assistants in specialized domains like edge computing lies not in their standalone intelligence, but in their integration with a tool-rich development environment. Platforms that provide agents with structured interfaces like CLIs and domain-specific 'skills', in addition to documentation, will see significantly better performance and efficiency than those relying on unstructured knowledge alone.