#multi-Agent
1352 related articles
·3 min
OpenClaw Multi-Agent AI Programming Workflow in Practice: From Coder to Manager
Deep dive into OpenClaw multi-agent AI programming workflows: context layering, CMUX parallel terminal management, work trees, and manager-perspective debiasing for scalable AI dev 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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·3 min
Cosmonapse: A Decentralized Multi-Agent Framework Built on an Event Bus
Cosmonapse is an open-source multi-agent framework that replaces central orchestrators with peer nodes, using typed signals and an event bus to fully decouple tool calls, memory, and HITL. Supports Python and TypeScript under Apache 2.0.
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·3 min
Coze Deep Dive: Multi-Agent Collaboration Platform Features & Usage Guide
A comprehensive guide to Coze by ByteDance: multi-agent collaboration, local tool integration, cross-platform sync, and credit system. Compare with Dify to get started fast.
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·2 min
LangGraph Multi-Agent Architecture in Practice: From Core Components to Production Deployment
A deep dive into LangGraph multi-agent architecture — covering hierarchical, network, and pipeline patterns with three hands-on projects using LangGraph 0.3.
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·3 min
Coze Deep Dive: Multi-Agent Collaboration Platform Architecture and Usage Guide
Deep dive into Coze's three core capabilities: multi-person multi-AI collaboration, customizable agents, and cross-platform project management. Covers credits, Dify comparison, and a practical learning path.
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·3 min
Coze Deep Dive: Core Capabilities and Tips for a Multi-Agent Collaboration Platform
A deep dive into Coze 3.0's multi-agent collaboration, covering project workspace architecture, credit economics, local tool integration, and a Dify comparison.
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·4 min
Loop Engineering in Practice: Designing and Deploying a Multi-Agent Collaborative Development System
A deep dive into Loop Engineering: how multi-agent collaborative dev systems achieve automated coding loops through workflow scheduling, step isolation, and validation.
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·2 min
GPT-5.6 Soul In-Depth Review: Can Multi-Agent Programming Mode Reshape the AI Development Tools Landscape?
GPT-5.6 Soul review: Super Mode hits 91.9% on TerminalBench. We break down multi-agent scheduling, benchmark controversies, and real-world dev tool comparisons.
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·2 min
GPT-5.6 Deep Dive: Tiered Models + Multi-Agent Architecture, LLMs Evolve into Workflow Engines
GPT-5.6 isn't just a capability upgrade — it's an architectural shift: tiered models, programmatic tool calling, and multi-agent collaboration turn LLMs into workflow engines for production systems.
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·2 min
TradingAgents-astock: A Practical Guide to the Multi-Agent Research Framework for A-Share Markets
TradingAgents-astock is a multi-agent A-share research framework with free domestic data sources, seven debating analyst agents, and support for DeepSeek, Qwen, and more.
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·3 min
AI Teams in Action: How MiniMax M3 Uses Multi-Agent Collaboration to Reinvent Content Creation
MiniMax M3-powered AR assistant M-Code automates the full content creation pipeline through four specialized agents: planning, recording, drafting, and review.
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One Prompt, 50 Games: An Experiment in…
·3 min
One Prompt, 50 Games: An Experiment in Parallel Multi-Agent Orchestration with Claude
One developer used a single prompt to run dozens of Fable-5 agents in parallel, generating 50+ playable games in one day. A deep dive into parallel agent orchestration, Claude Code CLI, and the future of AI-driven software production.
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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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·2 min
When Does Multi-Agent Architecture Slow Down Your Workflow? A Single vs. Multi-Agent Comparison
Multi-agent architecture isn't always better. This article analyzes how splitting tasks across agents introduces latency, token costs, and error propagation — with a practical framework for deciding when to use single vs. multi-agent design.
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PlanWright: A Control Plane and Multi-…
·2 min
PlanWright: A Control Plane and Multi-Agent Orchestration Layer for AI Coding Agents
PlanWright is a control plane for AI coding agents, drawing on Kubernetes orchestration principles to tackle multi-agent task assignment, state tracking, and collaboration conflicts.
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·3 min
AgentScope 2.0 Deep Dive: Six Core Upgrades for Production-Grade Multi-Agent Development
AgentScope 2.0 by Alibaba's Tongyi Lab delivers six major upgrades: typed event streaming, dangerous instruction interception, human-in-the-loop, concurrent execution, workspace system, and agent-as-a-service for production-grade multi-agent development.
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·3 min
The Deterministic Factual Substrate for Multi-Agent AI: A Deep Dive into Knowledge Kernel's Reproducible Grounding Design
A deep dive into how Knowledge Kernel builds a deterministic factual substrate for multi-agent AI through layered decoupling of reality, evidence, facts, and reasoning — with dataset_hash fingerprinting, atomic reloads, and observable telemetry.
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·3 min
LangChain V1.3 Hands-On Tutorial: A Complete Breakdown of RAG, Multi-Agents, and Engineering Mindset
An in-depth look at LangChain V1.3's core philosophy: from RAG to multi-agent workflows. Master LangGraph, Chain, and DeepAgent, learn token control and Human-in-the-loop, and become a true master of AI app development.
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·3 min
Adversarial RL: Why Are Critic Attacks Stronger in Multi-Agent Environments?
The classic Zhang et al. paper says Critic attacks are weaker than Actor attacks, but an experimenter observed the opposite in multi-agent PPO. This article dives into SA-MDP, continuous action spaces, and multi-agent non-stationarity in adversarial RL.
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