#Multi-Agent architecture
1315 related articles
·3 min
From Frontend to Agent Development: A Complete 6-Week Systematic Learning Path
A 6-week systematic learning path for frontend engineers transitioning to AI Agent development, covering core architecture, ReAct, multi-agent collaboration, RAG integration, and deployment.
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·3 min
Deconstructing Agents: Task Decomposition, Context Compression, and the Case Against Heavy Frameworks
A deep engineering analysis of Agent internals: how LLMs decompose tasks via tool calling, why context compression and memory are essential, and why solo developers should avoid heavy frameworks.
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·2 min
LLM Agent Long-Term Memory Security: A Six-Stage Attack Surface and Defense Framework
Deep analysis of LLM agent long-term memory security threats, covering persistence, statefulness, and propagation of memory poisoning, with a six-stage lifecycle defense framework.
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·2 min
Claude as Music Partner: The AGI Moment of AI Paired Creation
A developer added a DAW to their agentic dev environment with Claude, then paired with AI to finish music — experiencing a true AGI moment in creative collaboration.
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·5 min
The Five Stages of AI Agent Architecture Evolution: The Real Path from Model Calls to Production Runtime
Deep dive into the five evolution stages of AI Agent architecture: model calls, tool calls, workflows, Agent loops, and production runtime. Learn the responsibility boundaries and design principles.
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·4 min
AI Agent Development in Practice: A Complete Path from Zero to Production
A systematic guide to AI Agent development covering core modules, framework selection, tool calling, data preparation, and production deployment to help developers build production-ready Agent applications.
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·4 min
A Beginner's Guide to AI Agents: Core Principles and Learning Paths Explained
A beginner's guide to AI Agents: understand core principles, how Agents differ from LLMs, their execution mechanisms, and get tailored learning path recommendations.
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·3 min
Agent Skills Explained: Plug-and-Play Skill Packs for AI
A deep dive into Agent Skills architecture: modular design, progressive disclosure mechanism, and how it differs from Multi-Agent systems for AI capability extension.
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·5 min
Complete Breakdown of Core Competencies for AI Agent Engineers: From Demo to Production-Grade Systems
Deep breakdown of 4 core AI Agent engineer competencies: business decomposition, multi-Agent architecture, quantitative evaluation, and engineering delivery—bridging the gap from Demo to production.
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·5 min
The Complete Guide to AI Agent Development: A Four-Stage Progressive Roadmap
A systematic guide to AI Agent development across four stages: LLM fundamentals, ReAct paradigm, memory & tools, and multi-agent collaboration for developers.
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·5 min
Will Chinese Open-Source Models Burst the US AI Bubble? A Deep Dive into the Transmission Chain
Chinese open-source models like Kimi K3 and DeepSeek approach US closed-source performance at a fraction of the cost. This deep dive analyzes the transmission chain from price competition to valuation reassessment.
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·3 min
Cursor Selects Grok but Calls Opus: Subagent Model Substitution and Cost Control Issues Explained
Cursor users selecting Grok 4.5 find subagents secretly calling expensive Opus 5, consuming 11% quota per prompt. Analysis of model decoupling, cost transparency, and user strategies.
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·4 min
The More Complex the AI Agent, the More It Hallucinates? The Hidden Cost of Architectural Complexity
Why do AI Agents hallucinate more as they grow more complex? This article analyzes the causes from error accumulation, context noise, and model completion nature, with 5 practical production strategies.
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·3 min
Claude Opus 5 High Reasoning Mode: The Concerns and Insights of Overthinking
Claude Opus 5's high+ reasoning mode has been jokingly called an "anxious overthinker." This article analyzes why LLMs over-reason, the diminishing returns tipping point, and how to balance reasoning intensity.
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·3 min
Build RAG and AI Agent Projects at Zero Cost: A Practical Guide to Open-Source Tools
Build high-quality AI projects on a budget. Learn how to use Ollama, Groq, Chroma, and other free open-source tools to build RAG systems and multi-Agent workflows from scratch.
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·3 min
Build RAG and AI Agent Projects at Zero Cost: A Practical Guide to Open-Source Tools
Build high-quality AI projects on a budget. Learn how to use Ollama, Groq, Chroma, and other free open-source tools to build RAG systems and multi-Agent workflows from scratch.
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·4 min
Claude Code Tutorial: Environment Setup, Command Reference & Git Workflow in Practice
Complete guide to Claude Code covering CLI installation, domestic model switching, core commands, Git automation workflows, and automated code review and fix loops for enterprise projects.
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·4 min
GenAI Job Interview Gone Wrong: Interviewer Googles Gemini for Questions on the Spot — What's Broken in AI Hiring?
A fresh grad interviewing for a GenAI Trainer role faced prime number coding and activation function questions while the interviewer used Gemini to generate questions live — exposing AI hiring chaos.
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·3 min
AI Talent Surplus with No Problems to Solve? The Structural Mismatch in Enterprise AI Adoption
Companies race to hire AI talent, but do traditional organizations have enough AI problems to solve? This article examines the structural mismatch in enterprise AI adoption and offers pragmatic strategy advice.
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·4 min
AI Coding Tools in Practice: Which Ones Actually Stuck with the Team?
A 12-person product team shares real-world experiences with Cursor, Codex, Claude Code, and CodeRabbit—exploring efficiency plateaus, scenario matching, and selection criteria for AI coding tools that actually stick.
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