What if your computer-use agent could learn a new Command Line Interface (CLI)—and operate it safely without ever writing files or free-typing shell commands?...

What if your computer-use agent could learn a new Command Line Interface (CLI)—and operate it safely without ever writing files or free-typing shell commands? In Part 1 of our series on building a computer use agent, we built a custom Bash computer-use agent using NVIDIA Nemotron in just one hour. In this sequel, we’ll take it further by teaching the same reasoning model with no prior…

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Building an agent is more than just “call an API”—it requires stitching together retrieval, speech, safety, and reasoning components so they behave like...

Building an agent is more than just “call an API”—it requires stitching together retrieval, speech, safety, and reasoning components so they behave like one cohesive system. Each layer has its own interface, latency constraints, and integration challenges, and you start to feel them as soon as you move beyond a simple prototype. In this tutorial, you’ll learn how to build a voice-powered RAG…

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Agentic AI systems increasingly rely on collections of cooperating agents—retrievers, planners, tool executors, verifiers—working together across large...

Agentic AI systems increasingly rely on collections of cooperating agents—retrievers, planners, tool executors, verifiers—working together across large contexts and long time spans. These systems demand models that deliver fast throughput, strong reasoning accuracy, and persistent coherence over large inputs. They also require a level of openness that allows developers to customize, extend…

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