#agent-to-agent communication
29 related articles
·2 min
From Workflow Graphs to Distributed Protocols: Dissecting Multi-Agent System Architecture Paradigms
How does Cosmonapse replace LangGraph's graph structure with event-driven distributed protocols? A deep dive into two multi-agent architecture paradigms, their trade-offs, and when to use each.
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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
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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·3 min
Complete AI Agent Development Learning Path: From Core Principles to Enterprise Deployment
A structured AI Agent learning path covering core principles, prompt engineering, tool use, multi-agent systems, and frameworks like LangChain, CrewAI, and Dify for enterprise deployment.
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·4 min
The Three Eras of AI Agents: The Capability Leap from Tool Calling to Autonomous Orchestration
An in-depth look at the three core eras of AI Agent development: reliable tool calling, coherent long-task execution, and autonomous orchestration with metacognition. Helps developers match tasks to model capabilities.
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·7 min
A New Core Skill for Programmers: How to Effectively Lead Your AI Agent Dev Squad
Coding alone isn't enough anymore. Learn the 5 key steps to commanding AI Agents—define outcomes, split tasks, provide context, iterate small, and keep humans in the loop.
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·4 min
OpenAI Agents SDK in Practice: Harness and Sandbox Separation Architecture Explained
Deep dive into OpenAI Agents SDK updates covering Harness-Compute separation, Codex-style orchestration, sandbox snapshots, skills system, and multi-agent collaboration with practical demos.
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·2 min
When Millions of AI Agents Meet: A Deep Dive into Distributed Intelligence Collaboration and Security Challenges
Deep dive into AI Agent era challenges: multi-Agent collaboration, delegation mechanisms, agentic traps, cybersecurity threats, cognitive monoculture risks, and distributed intelligence as a new path to AGI.
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·3 min
Getting Started with AI Agent Development: Core Concepts, Architecture, and Practical Essentials
A comprehensive guide to AI Agent development covering core concepts, the Perception-Brain-Action architecture, key differences from chatbots, four essential components, and mainstream framework selection.
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·4 min
Complete Guide to Commercial AI Agent Development: From Requirements Analysis to Production Deployment
Complete guide to commercial AI agent development from scratch, covering requirements analysis, architecture design (ReAct framework, deep search, intent recognition), hands-on Coze platform implementation, workflow creation, and production deployment.
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·3 min
Multi-Agent Communication & Collaboration in Feishu: A Complete Guide to Configuration and Group Chat Orchestration
Learn how to configure Open Cloud for multi-Agent communication, including session_visibility, agent_to_agent toggle, and whitelist setup, plus Feishu group chat orchestration for AI team collaboration.
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·3 min
Getting Started with AI Agents: A Complete Learning Path from Zero to Production
A comprehensive guide to AI Agent architecture covering ReAct paradigm, multi-agent collaboration, RAG integration, and the planning-memory-tools framework, with a complete learning path from concepts to production deployment.
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·2 min
The Five-Layer Evolution of Scaling Law: How Physical AI Opens the Next Growth Curve
Deep analysis of Scaling Law's five-layer evolution from Pre-Training to Multi-Agent, exploring Physical AI's World Models, edge inference, and emotional interaction.
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·3 min
LangGraph Core Explained: Its Relationship with LangChain and Multi-Agent Orchestration Principles
Deep dive into LangGraph's core positioning, its relationship with LangChain, practical code comparisons of Chain vs Graph, understanding Agent essentials, and multi-agent orchestration design.
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Industry Insights·3 min
A2A Intelligent Trading Platform: A New Business Model Where AI Agents Automatically Take Orders and Earn Money
Deep dive into Yoyomit's A2A intelligent trading platform—the world's first marketplace where AI Agents automatically trade, take orders, and settle payments with 95% zero human intervention.
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Tutorials·3 min
Spring AI Agent Utils: A Java Agent Toolkit Reverse-Engineered from Claude Code's Core Features
Deep dive into Spring AI Agent Utils toolkit covering Skill modules, Ask a User Question, To Do Write, Auto Memory, and multi-Agent orchestration — empowering Java developers to build powerful AI Agents.
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Tutorials·2 min
MCP Protocol Practical Guide: The Standard Interface for Connecting LLMs to Everything
Deep dive into MCP (Model Context Protocol) principles and practical applications. Learn how LLMs connect to external tools via MCP to become agents, covering Java tech stacks, MCP Server ecosystem, Cherry Studio demos, and A2A protocol comparison.
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Tutorials·2 min
Claude Code Sub-Agent: A Practical Guide to Multi-Agent Collaboration for Enhanced Development Efficiency
Deep dive into Claude Code Sub-Agent mechanism with a practical blog writing + Git commit case study, showing how multi-agent collaboration solves instruction loss and context bloat issues.
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Tutorials·2 min
The Six Key AI Agent Protocols Explained: MCP, A2A, UCP, AP2, A2UI, and AGUI
Deep dive into six core AI agent protocols: MCP, A2A, UCP, AP2, A2UI, and AGUI — covering tool integration, multi-agent collaboration, commerce, payments, and dynamic UI, with Google ADK examples.
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Product Reviews·2 min
AgentChat: An Instant Messaging Platform That Lets AI Agents Communicate Like Humans
AgentChat is a free instant messaging platform built for AI Agents, supporting one-on-one messaging, group chats, and contact management for cross-framework Agent collaboration.
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