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A Coding Implementation to Design an Enterprise AI Governance System Using OpenClaw Gateway Policy Engines, Approval Workflows and Auditable Agent Execution

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In this tutorial, we build an enterprise-grade AI governance system using OpenClaw and Python. We start by setting up the OpenClaw runtime and launching the OpenClaw Gateway so that our Python environment can interact with a real agent through the OpenClaw API. We then design a governance layer that classifies requests based on risk, enforces […]

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Meet OpenViking: An Open-Source Context Database that Brings Filesystem-Based Memory and Retrieval to AI Agent Systems like OpenClaw

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OpenViking is an open-source Context Database for AI Agents from Volcengine. The project is built around a simple architectural concept: agent systems should not treat context as a flat collection of text chunks. Instead, OpenViking organizes context through a file system paradigm, with the goal of making memory, resources, and skills manageable through a unified

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LangChain Releases Deep Agents: A Structured Runtime for Planning, Memory, and Context Isolation in Multi-Step AI Agents

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Most LLM agents work well for short tool-calling loops but start to break down when the task becomes multi-step, stateful, and artifact-heavy. LangChain’s Deep Agents is designed for that gap. The project is described by LangChain as an ‘agent harness‘: a standalone library built on top of LangChain’s agent building blocks and powered by the

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Garry Tan Releases gstack: An Open-Source Claude Code System for Planning, Code Review, QA, and Shipping

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What if AI-assisted coding became more reliable by separating product planning, engineering review, release, and QA into distinct operating modes? That is the idea behind Garry Tan’s gstack, an open-source toolkit that packages Claude Code into 8 opinionated workflow skills backed by a persistent browser runtime. The tookit describes itself as ‘Eight opinionated workflow skills

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Google DeepMind Introduces Aletheia: The AI Agent Moving from Math Competitions to Fully Autonomous Professional Research Discoveries

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Google DeepMind team has introduced Aletheia, a specialized AI agent designed to bridge the gap between competition-level math and professional research. While models achieved gold-medal standards at the 2025 International Mathematical Olympiad (IMO), research requires navigating vast literature and constructing long-horizon proofs. Aletheia solves this by iteratively generating, verifying, and revising solutions in natural language.

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A Beginner’s Guide to Building Autonomous AI Agents with MaxClaw

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Most AI tools forget you as soon as you close the browser window. The system begins all interactions with a new user. AI agents provide a solution to this problem because they handle their complete workflow through their system. MaxClaw is one of the best in this category. MiniMax developed this system which operates completely from the cloud space. The system

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Model Context Protocol (MCP) vs. AI Agent Skills: A Deep Dive into Structured Tools and Behavioral Guidance for LLMs

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In recent times, many developments in the agent ecosystem have focused on enabling AI agents to interact with external tools and access domain-specific knowledge more effectively. Two common approaches that have emerged are skills and MCPs. While they may appear similar at first, they differ in how they are set up, how they execute tasks,

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Stanford Researchers Release OpenJarvis: A Local-First Framework for Building On-Device Personal AI Agents with Tools, Memory, and Learning

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Stanford researchers have introduced OpenJarvis, an open-source framework for building personal AI agents that run entirely on-device. The project comes from Stanford’s Scaling Intelligence Lab and is presented as both a research platform and deployment-ready infrastructure for local-first AI systems. Its focus is not only model execution, but also the broader software stack required to

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How to Design a Streaming Decision Agent with Partial Reasoning, Online Replanning, and Reactive Mid-Execution Adaptation in Dynamic Environments

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In this tutorial, we build a Streaming Decision Agent that thinks and acts in an online, changing environment while continuously streaming safe, partial reasoning updates. We implement a dynamic grid world with moving obstacles and a shifting goal, then use an online A* planner in a receding-horizon loop to commit to only a few near-term

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NVIDIA Releases Nemotron 3 Super: A 120B Parameter Open-Source Hybrid Mamba-Attention MoE Model Delivering 5x Higher Throughput for Agentic AI

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The gap between proprietary frontier models and highly transparent open-source models is closing faster than ever. NVIDIA has officially pulled the curtain back on Nemotron 3 Super, a staggering 120 billion parameter reasoning model engineered specifically for complex multi-agent applications. Released today, Nemotron 3 Super sits perfectly between the lightweight 30 billion parameter Nemotron 3

NVIDIA Releases Nemotron 3 Super: A 120B Parameter Open-Source Hybrid Mamba-Attention MoE Model Delivering 5x Higher Throughput for Agentic AI Read More »