<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Multi-Agent-Systems on Noureddine RAMDI</title><link>https://ramdi.fr/tags/multi-agent-systems/</link><description>Recent content in Multi-Agent-Systems on Noureddine RAMDI</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 23 May 2026 20:41:27 +0000</lastBuildDate><atom:link href="https://ramdi.fr/tags/multi-agent-systems/index.xml" rel="self" type="application/rss+xml"/><item><title>Cairn: a blackboard-driven state-space search engine with stateless agent workers</title><link>https://ramdi.fr/github-stars/cairn-a-blackboard-driven-state-space-search-engine-with-stateless-agent-workers/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/cairn-a-blackboard-driven-state-space-search-engine-with-stateless-agent-workers/</guid><description>Cairn implements state-space search via a minimal blackboard architecture with stateless OODA loop workers. It scored perfectly at the Tencent AI Penetration Testing Challenge.</description></item><item><title>Inside red-run: AI agent orchestration for offensive security assessments</title><link>https://ramdi.fr/github-stars/inside-red-run-ai-agent-orchestration-for-offensive-security-assessments/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-red-run-ai-agent-orchestration-for-offensive-security-assessments/</guid><description>red-run orchestrates Claude Code AI agent teams across the full pentest kill chain using persistent teammates and semantic routing. Explore its architecture, strengths, and quickstart.</description></item><item><title>OpenClaw Agents: orchestrating adversarial AI agents with shell-driven provisioning</title><link>https://ramdi.fr/github-stars/openclaw-agents-orchestrating-adversarial-ai-agents-with-shell-driven-provisioning/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/openclaw-agents-orchestrating-adversarial-ai-agents-with-shell-driven-provisioning/</guid><description>OpenClaw Agents deploys paired AI agents using shell scripts for adversarial collaboration in OpenClaw gateway, supporting multi-channel or local workflows with safe config merges.</description></item><item><title>Inside Claude Code: A detailed reconstruction of Anthropic's AI safety and architecture</title><link>https://ramdi.fr/github-stars/inside-claude-code-a-detailed-reconstruction-of-anthropic-s-ai-safety-and-architecture/</link><pubDate>Tue, 05 May 2026 16:46:42 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-claude-code-a-detailed-reconstruction-of-anthropic-s-ai-safety-and-architecture/</guid><description>A deep dive into Claude Code’s 512K lines of TypeScript reveals a layered YOLO safety classifier, multi-agent IPC, and terminal UI rendering—key to Anthropic’s AI production system.</description></item><item><title>KohakuTerrarium: Modular AI agent composition with algebraic pipelines</title><link>https://ramdi.fr/github-stars/kohakuterrarium-modular-ai-agent-composition-with-algebraic-pipelines/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/kohakuterrarium-modular-ai-agent-composition-with-algebraic-pipelines/</guid><description>KohakuTerrarium offers a Python framework to build modular AI agents using a unique algebra for composing multi-agent pipelines, with session persistence and multi-runtime support.</description></item><item><title>Mapping the AI agent orchestration landscape with an awesome curated list</title><link>https://ramdi.fr/github-stars/mapping-the-ai-agent-orchestration-landscape-with-an-awesome-curated-list/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/mapping-the-ai-agent-orchestration-landscape-with-an-awesome-curated-list/</guid><description>A curated list catalogs 80+ AI coding agent orchestration tools, revealing a fragmented ecosystem around git worktree isolation, parallel execution, and multi-agent coordination.</description></item><item><title>Station: a Go runtime for multi-agent AI orchestration with MCP stdio bridging</title><link>https://ramdi.fr/github-stars/station-a-go-runtime-for-multi-agent-ai-orchestration-with-mcp-stdio-bridging/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/station-a-go-runtime-for-multi-agent-ai-orchestration-with-mcp-stdio-bridging/</guid><description>Station is an open-source Go runtime that orchestrates multi-agent AI systems on self-hosted infrastructure using a Git-backed workflow and MCP stdio bridging. It supports 41 AI tools and multiple AI providers.</description></item><item><title>LobeHub: An extensible AI agent playground with MCP plugin architecture</title><link>https://ramdi.fr/github-stars/lobehub-an-extensible-ai-agent-playground-with-mcp-plugin-architecture/</link><pubDate>Sat, 02 May 2026 20:15:49 +0000</pubDate><guid>https://ramdi.fr/github-stars/lobehub-an-extensible-ai-agent-playground-with-mcp-plugin-architecture/</guid><description>LobeHub offers a TypeScript-based AI agent platform with a unique MCP plugin system for integrating 10,000+ skills and collaborative multi-agent workflows. Explore its architecture and developer experience.</description></item><item><title>Agno: Building production-ready agentic software with minimal code</title><link>https://ramdi.fr/github-stars/agno-building-production-ready-agentic-software-with-minimal-code/</link><pubDate>Sat, 02 May 2026 20:07:04 +0000</pubDate><guid>https://ramdi.fr/github-stars/agno-building-production-ready-agentic-software-with-minimal-code/</guid><description>Agno provides a minimal, production-ready Python framework for scalable agentic software with per-user isolation and native tracing in ~20 lines of code.</description></item></channel></rss>