Uploaded April 2026 | Updated September 2026, 2 weeks ago
Open source thrives on collaboration. In this session, we’ll walk through how to contribute to an open-source project by working directly on NVIDIA NemoClaw — an open‑source reference stack for running OpenClaw autonomous agents inside NVIDIA OpenShell’s sandboxed environment. You’ll see the full process: forking the repo, building locally, implementing a feature, writing tests, and opening a pull request. We’ll also show how to submit feature requests and ideas through GitHub to help shape the NVIDIA NemoClaw roadmap and community priorities.
What you’ll learn:
- How to set up your environment and explore the NVIDIA NemoClaw codebase.
- How to contribute a change: branching, testing, and submitting a pull request.
- How to open a feature request or discussion directly on GitHub.
-How community feedback and contributions influence the NVIDIA NemoClaw roadmap.
Join us live as we add a new feature to NVIDIA NemoClaw, answer your questions, and show how developers can actively shape open‑source AI projects from code to community.
Open source thrives on collaboration. In this session, we’ll walk through how to contribute to an open-source project by working directly on NVIDIA NemoClaw — an open‑source reference stack for running OpenClaw autonomous agents inside NVIDIA OpenShell’s sandboxed environment. You’ll see the full process: forking the repo, building locally, implementing a feature, writing tests, and opening a pull request. We’ll also show how to submit feature requests and ideas through GitHub to help shape the NVIDIA NemoClaw roadmap and community priorities.
What you’ll learn:
- How to set up your environment and explore the NVIDIA NemoClaw codebase.
- How to contribute a change: branching, testing, and submitting a pull request.
- How to open a feature request or discussion directly on GitHub.
-How community feedback and contributions influence the NVIDIA NemoClaw roadmap.
Join us live as we add a new feature to NVIDIA NemoClaw, answer your questions, and show how developers can actively shape open‑source AI projects from code to community.
