#agent collaboration
180 related articles
Tutorials
Spring AI Agent Utils: A Java Agent To…
·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
Harness Engineering Deep Dive: Multi-L…
·2 min
Harness Engineering Deep Dive: Multi-Level Memory and Multi-Agent Collaborative Development in Practice
Deep dive into Harness Engineering: deconstructing Claude Code's multi-level memory, defense-in-depth, Hermes Agent autonomous evolution, and multi-Agent collaboration for industrial-grade AI development.
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Tutorials
Context Engineering Replaces Prompt En…
·1 min
Context Engineering Replaces Prompt Engineering: A Guide to Boosting Programming Efficiency with Claude Code
Learn how Context Engineering replaces Prompt Engineering to boost Claude Code efficiency. Build complex multi-Agent projects with zero coding using structured context files.
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Industry Insights
AI Fully Automated Orchestration in Pr…
·3 min
AI Fully Automated Orchestration in Practice: How Software Production Costs Are Being Completely Disrupted
Deep analysis of AI fully automated software orchestration: from Claude Code workflows to parallel orchestration strategies, exploring how models like MiniMax M1 drive software production costs toward zero.
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Tutorials
MCP Protocol Practical Guide: The Stan…
·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
CrewAI Multi-Agent Collaboration in Pr…
·2 min
CrewAI Multi-Agent Collaboration in Practice: Core Concepts, Model Comparison & API Deployment
A deep dive into CrewAI's four core concepts for multi-agent collaboration, with hands-on FastAPI deployment and a comparison of GPT-4o-mini, Qwen MAX, and Llama 3.1.
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Tutorials
Practical Guide to Building Multi-Agen…
·3 min
Practical Guide to Building Multi-Agent Collaborative Applications with CrewAI + FastAPI
Learn how to build a multi-Agent collaborative system with CrewAI and FastAPI. Covers Agent, Task, Crew concepts, GPT/Tongyi Qianwen/Ollama integration, with complete code examples and model comparisons.
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Tutorials
WenzAgent Open-Source Framework: A Pra…
·2 min
WenzAgent Open-Source Framework: A Practical Tutorial for Multi-Agent Collaborative Management on LAN
A detailed guide on deploying WenzAgent, an open-source multi-Agent management framework under Apache License, supporting LAN-based multi-device AI agent collaboration with Server-Client architecture.
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Tutorials
Building an Agent Framework from Scrat…
·2 min
Building an Agent Framework from Scratch: Breaking Down the Four Core Modules with Code Implementation
Learn how to split AI Agent capabilities into four modules—Tool Registry, Message Store, Agent Runtime, and Built-in Tools—and build a reusable, extensible Agent framework using Python decorators.
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Tutorials
Getting Started with LangChain: Core C…
·3 min
Getting Started with LangChain: Core Concepts and Hands-On Guide for LLM and Agent Development
A systematic guide to LangChain's core features, covering LLM vs. Agent concepts, unified interface design, multi-provider support, environment setup, and hands-on code examples for AI app development.
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Tutorials
AI Agent Learning Roadmap: From Beginn…
·3 min
AI Agent Learning Roadmap: From Beginner to Enterprise-Level Development in Three Months
A detailed three-month AI Agent learning roadmap covering LLM basics, ReAct paradigm, LangChain, memory mechanisms, tool calling, and multi-agent collaboration with practical project suggestions.
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Product Reviews
Cursor 2.0 In-Depth Review: Five Major…
·3 min
Cursor 2.0 In-Depth Review: Five Major New Features Including Custom Model, Multi-Agent Parallelism, and More
In-depth analysis of Cursor 2.0's five core updates: custom Composer model speed tests, Git Worktrees multi-agent parallel development, built-in browser, and a three-model comparison of Claude, GPT-5, and Composer.
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Tutorials
Harness Engineering: A Practical Guide…
·3 min
Harness Engineering: A Practical Guide to AI Programming — From Prompts to Mastery
Explore the three stages of AI programming evolution: from Prompt Engineering to Context Engineering to Harness Engineering. Master enterprise-grade AI coding with Cloud Code + VS Code.
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Tutorials
Cursor Multi-Agent Workflow: A Practic…
·3 min
Cursor Multi-Agent Workflow: A Practical Guide to Main Thread & Grunt Collaboration
Learn the Cursor "Main Thread & Grunt" multi-agent workflow: use a high-tier model for complex tasks and a low-tier model for simple tasks in parallel to maximize AI coding efficiency.
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Industry Insights·3 min
AI Agents Deep Dive: The Paradigm Shift from Chat Tools to Autonomous Execution Systems
Deep analysis of AI Agents vs LLMs, covering three evolution stages, four core architecture components, three penetration paths, multi-agent collaboration, and societal impact.
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Product Reviews
Zenflow Hands-On Review: Spec-Driven A…
·3 min
Zenflow Hands-On Review: Spec-Driven AI Coding vs. Pure Prompt-Based Development
In-depth review of Zenflow's spec-driven AI coding vs Google AI Studio's prompt-based approach. Covers multi-agent execution, automated validation, version rollback, and the paradigm shift in AI programming.
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Industry Insights
US vs. China AI Computer Control Diver…
·3 min
US vs. China AI Computer Control Divergence: Why Programming Tools Still Haven't Integrated GUI Agents
AI computer control success rates surpass humans, yet Cursor and Copilot still lack GUI Agent integration. Deep analysis of US product packaging vs. China's open-source ecosystem, plus three bottlenecks blocking the path to autonomous software engineers.
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Tutorials·3 min
LangGraph Multi-Agent Architecture: Graph Structure Principles and Enterprise-Level Implementation Guide
Deep dive into LangGraph's core graph structure design, single and multi-agent collaboration patterns, MCP protocol integration, and Time Travel fault-tolerance, with enterprise-level hybrid multi-agent architecture implementation.
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Product Reviews
Warp 2.0 Deep Dive: An AI Development …
·3 min
Warp 2.0 Deep Dive: An AI Development Environment with Multi-Agent Parallelism
Deep dive into Warp 2.0's Agent Development Environment (ADE): multi-agent parallel orchestration, terminal editor, AI coding platform, hands-on SaaS app building, and comparison with Cursor and Claude Code.
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Tutorials·3 min
LangGraph Multi-Agent Architecture: Core Principles and Enterprise-Level Implementation Guide
Deep dive into LangGraph multi-agent architecture covering Graph structure principles, MCP service integration, Time Travel debugging, and supervised multi-agent enterprise implementation patterns.
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