#Agent
970 related articles
Tutorials·3 min
Enterprise Multi-Agent Development: Low-Code Platforms vs. Hand-Written Code — An In-Depth Comparison
In-depth comparison of two enterprise multi-agent development approaches: low-code platforms like Dify vs. hand-written code with LangGraph. Covers efficiency, flexibility, security, and prompt injection defense strategies.
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Tutorials·3 min
LangChain Core Concepts Explained: A Complete Guide to Components, Chains, and Agents
Deep dive into LangChain's three core concepts—Components, Chains, and Agents. Learn how this open-source framework connects LLMs to the external world and helps developers build enterprise AI apps.
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Tutorials·3 min
RAG Technology Full-Stack Analysis: Core Principles, Enterprise Implementation & Learning Path
Deep analysis of RAG technology's core principles, three key values, enterprise implementation cases, common pitfalls, and a systematic learning roadmap covering vector databases, retrieval optimization, and Knowledge Graph fusion.
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Product Reviews·3 min
Kimi K2.6 In-Depth Review: A Complete Breakdown of Its Coding and Agent Capabilities
In-depth review of Kimi K2.6's coding, Agent collaboration, and visual development capabilities. #1 open-source on SWE-Bench Pro, 300 parallel sub-agents, API priced at 1/3 of competitors.
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Tutorials·2 min
Huawei Hermes Agent Manual Explained: Five-Layer Memory Architecture and Multi-Agent Collaboration in Practice
Deep dive into Huawei's 100-page Hermes Agent manual: five-layer memory architecture solving AI amnesia, self-evolution loops for continuous optimization, and multi-agent collaboration engineering.
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Tech Frontiers·2 min
Kimi K2.5 Fully Open-Sourced: Deep Dive into 1T Parameter MoE Architecture + Agent Cluster Capabilities
Deep dive into Moonshot AI's fully open-sourced Kimi K2.5: 1T parameter MoE architecture, Vision-to-Code capabilities, and 100-Agent parallel cluster system topping open-source benchmarks.
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Tutorials·3 min
Enterprise RAG Implementation: Architecture Principles and Production-Grade Optimization Guide
Complete guide to enterprise RAG architecture covering data indexing, vectorization, and retrieval optimization. Practical insights on chunking strategies, hybrid retrieval, and hallucination control for production-grade LLM applications.
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Tutorials·3 min
Getting Started with LLM Application Development from Scratch: A Complete Guide to Learning Paths and Career Directions
A complete beginner's guide to LLM application development: learn the three key directions (API calling, RAG, Agent), master frameworks like LangChain, and follow a step-by-step learning path to become an AI application developer.
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Tutorials·3 min
Learning LLM Application Development from Scratch: A Complete Roadmap from RAG to Agent
How to start LLM application development from scratch? A complete roadmap covering Python basics, RAG knowledge bases, and Agent development with LangChain.
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Tutorials·3 min
Deep Agents: Enterprise-Grade Agent Engineering and Deep Research Implementation Guide
Learn how the Deep Agents framework solves enterprise AI Agent challenges like tool sprawl and context pollution, with a complete Deep Research implementation guide covering task decomposition, multi-source integration, and structured report generation.
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Tutorials
GStack Tutorial: 23 Commands That Give…
·3 min
GStack Tutorial: 23 Commands That Give One Person an Entire AI Development Team
Deep dive into GStack, the open-source toolkit by YC President Gary Tan. 23 slash commands turn Claude Code into a full AI dev team covering product decisions to deployment.
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Tutorials
Decoding LLM Naming Conventions: Param…
·3 min
Decoding LLM Naming Conventions: Parameter Counts, Quantization Formats & VRAM Requirements Quick Reference
Decode LLM naming conventions, understand 32B parameters & AWQ/GGUF quantization formats, with 4-bit VRAM estimation formulas, MOE model pitfalls, and model selection by GPU tier.
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Tutorials
One Command to Use GPT-5.5 for Free wi…
·2 min
One Command to Use GPT-5.5 for Free with OpenClaw
Learn how to configure OpenClaw AI coding assistant with one command to call OpenAI's GPT-5.5 model via the Codex plugin, reusing your GPT membership at zero extra cost.
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Industry Insights
You Don't Need to Start an Agency to B…
·3 min
You Don't Need to Start an Agency to Break Into AI: The Most Underrated AI Career Opportunity
76% of large enterprises are establishing Chief AI Officers, but you don't need to be a CAIO to seize AI career opportunities. Discover two proven paths into AI leadership roles.
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Product Reviews
AI Coding Appliance vs Cloud LLMs: Can…
·2 min
AI Coding Appliance vs Cloud LLMs: Can ¥480K in Annual Fees Buy 4 Local Deployment Solutions?
A deep cost comparison between AI coding appliances and cloud LLM APIs. A 20-person team spending ¥480K/year on tokens can deploy 4 local OnePanel units at ¥99K each, breaking even in 2.5 months.
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Tutorials
Enterprise AI Agent Four-Layer Archite…
·3 min
Enterprise AI Agent Four-Layer Architecture Design and PDCA Continuous Optimization Practical Guide
Deep dive into enterprise AI Agent four-layer architecture design (User, Gateway, Agent Service, Capability layers) with PDCA optimization methodology and dual manual+automated evaluation for production-grade Agent systems.
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Tutorials
Frontend to AI Full-Stack: Complete Sk…
·2 min
Frontend to AI Full-Stack: Complete Skill Tree & Learning Roadmap
A complete skill tree for frontend developers transitioning to AI full-stack engineers, covering TypeScript, NestJS, LangChain JS, RAG, vector databases, and Tauri 2 with a clear learning roadmap.
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Tutorials
Claude Code + Skills: A Practical Guid…
·3 min
Claude Code + Skills: A Practical Guide to 10x AI-Driven Test Case Generation
Learn how Claude Code combined with Skills encapsulation enables AI-driven test case generation with 10x efficiency gains, from 33 to 400+ cases through encoded expert knowledge.
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Tutorials
Agent Loop Explained: Solving Code Ref…
·3 min
Agent Loop Explained: Solving Code Refactoring Pain Points with the ReAct Pattern
Deep dive into Agent Loop, the core mechanism of AI coding tools. Learn how the ReAct pattern's reason-act-observe cycle enables autonomous multi-step code refactoring.
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Tutorials
Running Out of Codex Credits? AnySearc…
·2 min
Running Out of Codex Credits? AnySearch Skill Saves You Massive Token Overhead
Real-world testing shows AnySearch Skill saves ~27% Token overhead for Codex while significantly improving search quality. Learn how it works, how to install it, and when to use it.
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