Train AI Agents for Command-Line Tasks with Synthetic Data and Reinforcement Learning & Gym | Nemotron Labs

What if your computer-use agent could learn a new command-line tool—operating it safely, without writing files or free-typing shell commands? With NVIDIA Nemotron open models, you can quickly train specialized agents for any CLI, using synthetic data and reinforcement learning no usage logs required.

Curious how it can be adapted for your own proprietary CLI environment? Join us live for a developer-focused livestream. In this interactive livestream, we’ll cover:

- A live demo: Generating synthetic training data using NeMo Data Designer, validating examples, and fine-tuning with techniques like LoRA and reinforcement learning with verifiable rewards (RLVR) using NeMo RL.

- Showcase how safety is built into every layer, from human-in-the-loop command approval to runtime isolation.

- Explain why synthetic data generation and RL accelerate agent specialization without compromising accuracy or trust.

Bring your questions about the workflow, model customization, and synthetic data generation, we’ll be answering them live throughout the livestream.