#LLM application layer
2272 related articles
Product Reviews·2 min
Kimi K2.6 In-Depth Review: Comprehensive Evaluation of Coding, Multi-Agent, and Frontend Development Capabilities
In-depth review of Kimi K2.6 open-source model across frontend development, multi-agent collaboration, and long-horizon tasks, covering four professional modes, 3D/SVG generation, and pricing analysis.
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Tutorials·3 min
Complete Breakdown of Andrew Ng's Agent Course: A Practical Guide to the Five Core Modules of AI Agent Development
Deep dive into Andrew Ng's viral AI Agent course covering five core modules: Reflection, Planning, Tool Use, Multi-Agent Collaboration, and Memory, with practical learning paths for LLM agent development.
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Tutorials·3 min
Complete Installation & Configuration Guide for VectCut AI Editing Agent: Windows & Mac
Complete guide to installing and configuring VectCut AI Editing Agent on Windows and Mac, covering client download, CapCut draft path setup, and Git Bash installation.
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Tutorials·3 min
Agent Skills Decision Trees: Enabling Autonomous Decision-Making for AI Coding Assistants
Learn how to embed decision tree logic in Agent Skills to give AI coding assistants like Antigravity and Claude Code autonomous decision-making. Includes a Code Review Router case study with complexity scoring and failover.
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Tutorials·3 min
Frontend Engineers Leveling Up to AI Agents: LangGraph.js Architecture Design & Practical Guide
How can frontend engineers advance into AI Agent development? This guide covers LangGraph.js core architecture (state, nodes, edges), LangChain comparison, and workflow agent design with practical examples.
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Tech Frontiers·3 min
Claude Code Sub-Agents and Cursor BugBot Launch: AI Programming Tools Get Major Upgrades
Anthropic adds custom sub-agents to Claude Code, Cursor launches code review Agent BugBot, Qwen releases 92-language translation model, and Google unveils three experimental AI products.
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Tutorials·2 min
The Three-Layer Pyramid Model for Agent Development: From Beginner to Industrial-Grade Deployment
Deep dive into the Three-Layer Pyramid Model for Agent development, covering autonomous agents, collaborative multi-agent systems, and universal orchestration agents with a complete learning path from beginner to industrial-grade deployment.
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Tutorials·3 min
Getting Started with AI Full-Stack Development: A Knowledge Framework from Machine Learning to Large Language Models
A systematic guide to the relationships between AI, machine learning, deep learning, and large language models, helping developers build a clear knowledge framework and find an efficient learning path.
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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·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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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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Industry Insights·2 min
NVIDIA Blackwell Sets New STAC-AI Records for Financial LLM Inference
NVIDIA Blackwell GPU sets new LLM inference records in STAC-AI financial benchmark. Explore Blackwell architecture advantages, TensorRT-LLM co-optimization, and LLM applications in trading and risk management.
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Tutorials·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·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·3 min
LLM Learning Roadmap: A Complete Guide from Beginner to Project Implementation Across Seven Core Modules
A systematic breakdown of seven core LLM learning modules covering environment setup, Prompt Engineering, RAG, Agents, dev frameworks, fine-tuning, and hands-on projects for developers.
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Product Reviews·3 min
Trae SOLO 2.0 Deep Dive: Generating a ChatGPT Website with a Single Sentence — How Well Does It Work?
Hands-on test of Trae SOLO 2.0's zero-code development: generating a ChatGPT-like website from a single sentence. Detailed review of requirements generation, auto-correction, UI quality, and backend limitations.
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Product Reviews·2 min
AI Coding Tools Keep Crashing When Building Websites? Root Cause Analysis & Practical Solutions
AI coding tools crashing when building websites? This article analyzes root causes including multi-window concurrency, API rate limiting, and network instability, with practical solutions.
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Product Reviews·2 min
GPT-5 Codex Deep Dive: 93% Token Savings But Tool Ecosystem Still Needs Work
Deep testing GPT-5 Codex: 93.7% Token savings on simple tasks with deeper reasoning on complex ones. But UI quality drops, search is poor, and tool ecosystem fragmentation remains a major issue.
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Tutorials·2 min
Deep Dive into OpenAI Codex Plugin System: Architecture, Installation, and Hands-On Development
Deep dive into OpenAI Codex plugin system architecture (Skills, Apps, MCP Server), four installation methods, and a macOS app development case study showing how plugins boost AI coding efficiency.
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