#multi-Agent systems
89 related articles
Expert Opinions·3 min
The Salary Ceiling for Agent Engineers: Two Critical Dividing Lines
Agent engineer salary gaps hinge on two dividing lines: real production deployment experience and depth of foundational theory including deep learning, fine-tuning, and reinforcement learning.
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Tutorials·3 min
OpenClaw + Claude Code Token-Saving Guide: Zero-Polling with Hooks Callbacks
How to solve high Token consumption when OpenClaw calls Claude Code. Achieve zero-polling with Stop Hook and Session End dual callbacks, combined with Agent Teams for fully automated dev workflows.
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Product Reviews·3 min
Mavis Hands-On Review: Multi-Agent Collaboration vs. Single Agent — A Comprehensive Comparison in Academic Research and Web Development
In-depth review of Mavis multi-agent platform across academic retrieval, literature review, and web development. Multi-agent mode significantly outperforms single agents in accuracy and reliability.
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Deep Dives
Deep Dive into Cursor Skills: From Fun…
·4 min
Deep Dive into Cursor Skills: From Function Call to Practice
Deep dive into Cursor Skills' underlying principles, from Function Call and MCP protocol to Workflow Agent, with Spring AI Alibaba practical demo for any LLM.
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Industry Insights·2 min
The AI Market Is Expanding Rapidly: Why a Growing Pie Matters More Than Fighting Over Slices
The global AI market is expanding at a CAGR exceeding 35%, creating new demand across nearly every segment. This article analyzes the core logic of AI's expanding market and key takeaways for practitioners and investors.
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Tech Frontiers
AI Weekly: Claude Code Review, Gemma 4…
·3 min
AI Weekly: Claude Code Review, Gemma 4 Leak & DeepSeek V4 Delayed
Weekly AI roundup: Anthropic launches Claude Code review, Google Gemma 4 leaks with MoE architecture, DeepSeek V4 delayed again, Microsoft Copilot Cowork reshapes collaboration, and OpenAI acquires PromptFool.
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Product Reviews
Ruflo: A Multi-Agent Orchestration Sol…
·3 min
Ruflo: A Multi-Agent Orchestration Solution That Turns Claude Code into a 100-Person AI Team
Ruflo is an open-source multi-agent orchestration platform that upgrades single-threaded Claude Code into a distributed AI dev team with 100+ specialized Agents and a SANA self-learning engine.
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Tech Frontiers·2 min
LFM2.5-8B-A1B: A MoE Model with 1.5B Active Parameters Delivering 4x Its Weight Class Performance
Liquid AI releases LFM2.5-8B-A1B, a MoE model with 8B total params but only 1.5B active, matching 6B-class models in tool calling. Supports 128K context, local deployment, multilingual, with SGLang Day-0 support.
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Tutorials
BMad-Method: Building an AI Agile Deve…
·3 min
BMad-Method: Building an AI Agile Development Team with a Multi-Agent Framework
Deep dive into BMad-Method, an open-source multi-agent framework simulating a full agile team—from business analysis to QA—supporting Claude Code, Cursor, and more.
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Product Reviews
Augment Remote Agent Hands-On: Running…
·3 min
Augment Remote Agent Hands-On: Running 10 Cloud AI Agents in Parallel for Programming
Hands-on review of Augment Remote Agent: 10 cloud AI Agents coding in parallel, covering bug fixes, PR generation, documentation, and more with detailed workflows and real-world examples.
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Tutorials
Claude Code Source Code Study Guide: E…
·3 min
Claude Code Source Code Study Guide: Efficiently Mastering Core AI Agent Development Architecture
Learn AI Agent development from Claude Code's 510K lines of source code, covering Agent Loop, context compression, multi-Agent orchestration, and two efficient study methods.
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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
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
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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Tech Frontiers·2 min
Meta Muse Spark Released: A Comprehensive Analysis of the Native Multimodal Reasoning Model
Meta Superintelligence Labs releases Muse Spark, a native multimodal reasoning model supporting visual chain of thought, tool-use, and multi-agent orchestration. Deep dive into its capabilities and competitive positioning.
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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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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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