#multi-agent AI system
1321 related articles
·3 min
The ISNAD Framework: Building a Trust Verification Layer for Multi-Agent AI Systems Using a Millennium-Old Scholarly Tradition
The ISNAD framework adapts Islamic chain-of-transmission verification to build a trust layer for multi-agent AI systems, focusing on claim verification over agent authentication to combat hallucinations and silent failures.
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·3 min
Multi-Agent AI Paper Writing System: A Full-Stack Breakdown of FastAPI + Vue3
A deep dive into an AI paper writing system built with FastAPI + Vue3, covering multi-agent collaboration, RAG, streaming output, and full academic workflow automation.
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·2 min
Karma: An AI Coding Agent Orchestration Tool for Building Multi-Agent Collaborative Systems
Karma is an orchestration layer for AI coding agent frameworks, solving multi-agent collaboration, task decomposition, state management, and observability challenges. Compatible with Aider, OpenHands, and more.
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·2 min
AI Agent Out of Control? A Practical Guide to Building Traceable Multi-Agent Systems
Agent loops burning money, bills spiking unexpectedly? This article breaks down a traceable multi-agent system covering loop detection, behavior classification, cost prediction, and self-healing.
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·4 min
AIML Capstone Project Selection: Is a Multi-Agent Debate System Worth Building?
Torn over your capstone topic? This article analyzes the academic value, feasibility, and innovation potential of a Multi-agent Debate system to help AIML students decide.
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·2 min
Zero-Cost Multi-Agent AI System: A Complete Breakdown of the Free-Tier Build
A CS student built a multi-agent AI system with memory, 8 sub-agents, and real-time web research using only free infrastructure like Cloudflare Workers and GitHub Actions. Full breakdown inside.
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Google Co-Scientist Explained: A Gemin…
·2 min
Google Co-Scientist Explained: A Gemini-Powered Multi-Agent AI Research System
Deep dive into Google's Co-Scientist: a Gemini-powered multi-agent AI system that autonomously generates hypotheses, conducts agent debates, and iteratively evolves research directions.
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·3 min
HiClaw Open-Source Multi-Agent Collaboration System: A New Paradigm for Human-AI Collaboration Based on the Matrix Protocol
Deep dive into HiClaw, an open-source multi-Agent OS built on the Matrix protocol for transparent, controllable human-AI task coordination with Human-in-the-Loop design.
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·3 min
Vibe Coding in Practice: A Junior Student Uses Cursor to Build a Multi-Agent System with 51 AI Officials Based on the Three Departments and Six Ministries Framework
A junior student uses Cursor and Vibe Coding to build a multi-agent system with 51 AI officials modeled on China's Three Departments and Six Ministries, featuring task distribution, approval workflows, and Token cost visualization.
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Deep Dives·3 min
Deep Dive into Pi's Swarm System: A Biology-Inspired Multi-Agent AI Programming Architecture
Deep dive into Pi's swarm system architecture (26K GitHub stars): scout, worker, and soldier ant roles, pheromone communication, adaptive concurrency control, and how multi-agent collaboration revolutionizes AI programming.
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Tutorials·3 min
Building an Automated Money-Making System with AI Agents: A Multi-Agent Hands-On Tutorial
Learn how to build a full-pipeline automated money-making system using Multi-Agent architecture, covering Customer Service Agent, Cashier Agent, Delivery Agent setup, workflow orchestration, RAG knowledge bases, and MCP tool calling.
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Product Reviews·3 min
Claude Code 2.1 Deep Dive: Hooks Automation, MCP Ecosystem & Multi-Agent Collaboration Fully Explained
Full breakdown of Claude Code 2.1: Opus 4.6 model upgrade, Hooks deterministic automation, Skills multi-agent collaboration, MCP tool chain integration, plus IDE shortcuts and practical commands.
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Tutorials·3 min
Open Code Practical Guide: Building an AI Coding Team with Multi-Agent Systems
Deep dive into Open Code's core architecture: main agents, sub-agents, Skills extensions, JWT security, and multi-platform deployment for building efficient AI coding teams.
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Deep Dives·1 min
Ralph Loop: The New AI Programming Paradigm That Beats Multi-Agent Systems Through Iterative Trial and Error
Ralph Loop is a 2025 AI programming paradigm: a memoryless AI Agent repeatedly reads the same Prompt, accumulates experience via file systems, beating multi-agent architectures through iterative loops.
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Tutorials·1 min
LangGraph 1.0.5 Tutorial: Master AI Agent Orchestration & Multi-Agent Systems in Six Lessons
Complete guide to LangGraph 1.0.5 tutorial series covering durable execution, memory management, Human in the Loop, streaming, time travel, and multi-agent collaboration.
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·3 min
Getting Started with MARL (Multi-Agent Reinforcement Learning): A Complete Path from Theory to Code
A systematic guide to learning MARL from theory to code, covering CleanRL, PettingZoo, PyMARL tools, IQL/VDN/QMIX/MADDPG algorithm progression, and practical tips for bridging theory and implementation.
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·2 min
AI Agents Running a Real Company: Experiment Results and Capability Boundary Analysis
What happens when AI agents are tasked with running a real company? This analysis examines agent performance, critical shortcomings, and practical enterprise deployment advice.
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·3 min
Graph Engineering: The Core Paradigm and Design Patterns for AI Agent Orchestration
Explore how graph engineering uses state machines and directed graph structures to constrain AI agent behavior, covering reflection, routing, human-in-the-loop, and parallel execution patterns.
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·3 min
Graph Engineering: The Core Paradigm and Design Patterns for AI Agent Orchestration
Deep dive into how graph engineering uses state machines and directed graphs to constrain AI agent behavior, covering reflection, routing, human-in-the-loop, and parallel execution patterns.
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·4 min
Tiling Window Management: A New Interaction Paradigm for Multi-Agent Conversations
Exploring tiling window management for multi-agent AI conversations: how it solves parallel monitoring and observability challenges, real-world limitations, and the evolution from chat boxes to control consoles.
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