# OpenShell Published articles for OpenShell. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Building a Memory-Driven Agent with NVIDIA NemoClaw DevFeed: [Building a Memory-Driven Agent with NVIDIA NemoClaw]() Original publisher: [Read original article]() Author: Tanya Lenz Published: 2026-09-04T18:04:55Z Content type: tutorial Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Architecture & Design](), [Authorization](), [Markdown]() Tags: [agentic-ai-generative-ai](), [ai-agent](), [build-ai-agents](), [developer-tools-techniques](), [enterprise](), [llms](), [memory](), [nemoclaw](), [openshell](), [retrieval](), [retrieval-augmented-generation-rag](), [security]() ### AI overview This tutorial describes building a memory-driven AI agent with NVIDIA NemoClaw for enterprise work. It presents a structured self model, separates evidence from derived knowledge and governed execution, and emphasizes retrieval, user corrections, security, and authorization. ### Source excerpt Enterprise work spans messages, decisions, projects, and obligations that change over time. An AI agent that starts without this context must reconstruct it... ## Where Security Fits in an AI Agent Stack DevFeed: [Where Security Fits in an AI Agent Stack]() Original publisher: [Read original article]() Author: Michelle Horton Published: 2026-08-21T13:00:00Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [AI Bots](), [Application Security]() Tags: [agentic-ai-generative-ai](), [ai-agent](), [ai-safety](), [ai-security](), [inference](), [nvidia-research](), [openshell](), [security](), [trustworthy-ai-cybersecurity]() ### AI overview The article explains where security controls fit in an emerging AI agent stack. It emphasizes runtime boundaries, scoped access, authorization, isolation, auditability, and defense in depth rather than relying solely on prompts, model safeguards, or harness logic. ### Source excerpt As AI agents become more capable and operate over longer horizons, building security and trust into the applications they power becomes increasingly important.... ## Six Agent Harness Capabilities for Higher Model Performance DevFeed: [Six Agent Harness Capabilities for Higher Model Performance]() Original publisher: [Read original article]() Author: Michelle Horton Published: 2026-07-27T09:00:00Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [AI Bots](), [Developer Tools](), [ai observability]() Tags: [agentic-ai-generative-ai](), [ai-agent](), [architecture](), [featured](), [framework](), [llms](), [open-source](), [openshell](), [orchestration](), [performance](), [python](), [security-for-ai](), [top-stories](), [trustworthy-ai-cybersecurity]() ### AI overview The article presents NVIDIA Labs Object-Oriented Agents (NOOA), a Python-based framework for building AI agents as single classes. It outlines six harness capabilities intended to improve model performance, including typed interfaces, live object references, code-based actions, programmable loops, explicit state, and model-callable APIs. ### Source excerpt Building a great AI agent isn't just about choosing the right models. The harness is the architecture surrounding the model. How it renders context, executes... ## Building an Analysis AI Agent for Industrial Alarm Management with NVIDIA Nemotron DevFeed: [Building an Analysis AI Agent for Industrial Alarm Management with NVIDIA Nemotron]() Original publisher: [Read original article]() Author: Tanya Lenz Published: 2026-07-07T17:00:00Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [AI Bots]() Tags: [agentic-ai-generative-ai](), [ai](), [ai-agent](), [build-ai-agents](), [developer-tools-techniques](), [featured](), [gpu](), [industrial-digitalization-digital-twin](), [llms](), [nemo](), [nemo-retriever](), [nemotron](), [nvidia](), [ocr](), [openshell]() ### AI overview The article describes an NVIDIA-based AI agent for analyzing industrial alarms. It gathers historical and playbook context, runs specialist checks such as anomaly detection and OCR, and returns structured recommendations through an HTTP endpoint. ### Source excerpt Industrial machinery generates more alarms than technicians can triage. For each important alarm requiring follow-up, the technician pulls historical context,... ## How to Govern Autonomous Agents in Enterprise AI Factories DevFeed: [How to Govern Autonomous Agents in Enterprise AI Factories]() Original publisher: [Read original article]() Author: Michelle Horton Published: 2026-06-29T15:50:13Z Content type: tutorial Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Artificial Intelligence](), [AI Factory](), [systems](), [vulnerability management](), [configuration](), [Network](), [SOC](), [ide](), [browser](), [Terminal]() Tags: [agentic-ai-generative-ai](), [agents](), [ai](), [ai-agent](), [ai-factory](), [architecture](), [autonomous](), [autonomous-agents](), [browser](), [data-center-cloud](), [enterprise](), [featured](), [ide](), [mlops](), [network](), [openshell](), [policy](), [soc](), [telemetry](), [vulnerability-management]() ### AI overview This tutorial presents NVIDIA's Secure Agent Workspace Reference Design for governing autonomous AI agents in enterprise environments. It explains how to separate the presentation layer from managed agent execution and enforce identity, network access, credentials, runtime policy, auditing, human review, and workspace isolation. ### Source excerpt AI agents are quickly moving beyond chat. They inspect code, run tests, read documents, search knowledge bases, query internal systems, and operate for hours on... ## DigitalOcean at NVIDIA GTC 2026: Building the AI Factory for the Agentic Era DevFeed: [DigitalOcean at NVIDIA GTC 2026: Building the AI Factory for the Agentic Era]() Original publisher: [Read original article]() Author: Vinay Kumar, DigitalOcean Chief Product & Technology Officer Published: 2026-03-16T20:35:55Z Content type: release Language: en Sources: [DigitalOcean]() Topics: [Artificial Intelligence](), [Inference](), [Nvidia](), [Cloud](), [model-deployment](), [Deployment](), [NemoClaw](), [OpenClaw](), [OpenShell](), [Open Source]() Tags: [2026](), [agentic](), [ai](), [announce](), [autonomous](), [deployment](), [digitalocean](), [inference](), [infrastructure](), [models](), [nemoclaw](), [nvidia](), [open-source](), [openclaw](), [openshell](), [product-updates](), [production](), [services]() ### AI overview DigitalOcean announces an expansion of its AI inference capabilities in partnership with NVIDIA. The article describes an AI Factory for production AI workloads, including agentic workflows, OpenClaw deployment, NemoClaw, and the OpenShell runtime. ### Source excerpt A seamless path for builders: Start building on build.nvidia.com, Deploy to DigitalOcean The landscape of artificial intelligence has shifted from static models to dynamic, long-running agents. At DigitalOcean, our mission is to provide developers with a purpose-built, agentic, inference cloud for running AI in production--without the operational overhead or complex cost structures of traditional infrastructure. Today, at NVIDIA GTC 2026, we are excited to announce a massive expansion of our inference capabilities in partnership with NVIDIA. We are moving beyond basic infrastructure; we are building an AI Factory designed specifically to support AI builders and power the next generation of autonomous agents. The Proven Home for AI Agents DigitalOcean is rapidly becoming the dominant player and preferred deployment destination for agentic workflows. When the open-source agent OpenClaw (formerly Clawdbot) went viral, we recognized the market's need for frictionless deployment. In under 36 hours, we shipped a production-ready 1-Click Droplet to our Marketplace. The results demonstrate our reach: OpenClaw has driven 43,000+ total deployments on DigitalOcean with over 11,000 active OpenClaw deployments in production today. Builders aren't just deploying models; they are utilizing our ecosystem, expanding into adjacent services like Backups, Snapshots, and Gradient AITM Serverless Inference to support their agentic workloads. DigitalOcean and NVIDIA are also working together on NVIDIA NemoClaw, an open source stack that simplifies running OpenClaw always-on assistants, more safely, with a single command. The NVIDIA OpenShell runtime offers a secure environment to run autonomous agents and open source models, then deploy seamlessly to DigitalOcean. Investing in the "AI Factory": Deep Cloud & Inference Integration Why is DigitalOcean uniquely positioned to win in this new marketplace? We are investing deeply to integrate traditional cloud primitives with our state-of-the-art