#LLM framework
3631 related articles
·2 min
The Five-Layer Evolution of Scaling Law: How Physical AI Opens the Next Growth Curve
Deep analysis of Scaling Law's five-layer evolution from Pre-Training to Multi-Agent, exploring Physical AI's World Models, edge inference, and emotional interaction.
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·4 min
What Is Cursor? A Complete Guide to the AI-Native Programming IDE's Core Features and Use Cases
Deep dive into Cursor's four core features: AI-native design, natural language code generation, context awareness, and multi-model switching. Compare it with traditional IDEs to see if Cursor can boost your dev efficiency.
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·4 min
Complete Beginner's Guide to Cursor AI: Three Modes Explained with Hands-On Demo
Learn Cursor AI editor setup, Agent/Ask/Manual modes, model selection tips, and build a full student management system from scratch in this step-by-step guide.
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·4 min
The Five-Tier Pyramid of IT Careers in the AI Era: Your Position Determines Your Career Ceiling
AI is reshaping IT careers into a five-tier pyramid from tool usage to self-developed models. Learn where you fit and how to maximize your career potential.
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·3 min
Claude Code Ultra Code in Practice: One Person Orchestrating 100+ Agents in Parallel Development
Learn how to use Claude Code's Ultra Code and Dynamic Workflow to orchestrate 100+ Agents in parallel, with Deep Research demos, token-saving tips, and workflow reuse methods.
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·3 min
Can AI Agents Replace Security Engineers? Insights from Coding Agents Reveal the Industry Truth
In-depth analysis of AI agents' real impact on cybersecurity. From chat tools to coding agents like Crawfish and Hermes, learn how AI is reshaping security engineering and how professionals should adapt.
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·2 min
Codex Systematic Tutorial: From Beginner to Enterprise-Level AI Engineering
In-depth guide to Codex AI programming tool: environment setup, Rules system, MCP protocol integration, multi-Agent collaboration, and enterprise RAG customer service project for complete AI engineering deployment.
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·2 min
Trae + Claude Code + DeepSeek: A Low-Cost AI Programming Combo Explained
A detailed guide to the Trae, Claude Code, and DeepSeek AI programming combo — just 20 RMB/week in API costs. Covers setup steps, practical tips, and layered collaboration strategies.
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·2 min
Codex and Claude Code Multi-Agent Collaboration: A Practical Guide to Team-Based Workflows
Learn how to make Codex and Claude Code collaborate like a team. Use a cloud Agent orchestrator, shared project spaces, and clear task division to build a multi-AI Agent team workflow.
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·2 min
Claude Code vs ByteDance Codex: A Guide to Chinese Learning Resources and Choosing the Right Tool
Compare Claude Code and ByteDance Codex: their positioning, core capabilities, and use cases. Includes Chinese learning resource recommendations and beginner path selection guide for AI programming.
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·3 min
AI Agent Productivity Guide for Developers: Practical Methods to Automate 84% of Non-Coding Work
Developers spend 84% of their time on non-coding tasks. Learn how to use AI Agents to automate Jira tickets, tech docs, and multi-project management with Claude Code and Tmux workflows.
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·4 min
AI Agent Core Architecture Explained: A Deep Dive into the Four Key Modules — Perception, Brain, Action, and Memory
Deep dive into AI Agent architecture: explore the four core modules — Perception, Brain, Action, and Memory — covering RAG, tool calling, Chain of Thought, and more.
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·3 min
Java Developer's Guide to AI Application Development: Career Path, Skills, and Hands-On Strategy
A practical guide for Java developers transitioning to AI app development. Includes a 45-day learning plan covering Spring AI, RAG, Agent skills, plus resume and interview strategies.
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·3 min
Three Essential Tools to Install Before Setting Up OpenAI Codex
Learn how to install and configure Git, Node.js, and VS Code before setting up OpenAI Codex. Complete guide with download steps, verification methods, and troubleshooting tips.
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·4 min
AI Large Language Model Learning Roadmap: A Complete Guide from Zero to Project Implementation
A systematic AI LLM learning roadmap covering prompt engineering, RAG, AI Agent development, and fine-tuning — with beginner-friendly paths and practical tips.
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·3 min
LangGraph Core Explained: Its Relationship with LangChain and Multi-Agent Orchestration Principles
Deep dive into LangGraph's core positioning, its relationship with LangChain, practical code comparisons of Chain vs Graph, understanding Agent essentials, and multi-agent orchestration design.
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·4 min
AI Agent Development Learning Roadmap: A Complete Four-Stage Plan from Zero to Production
A systematic AI Agent development learning roadmap covering LLM API calls, ReAct framework, memory mechanisms, and multi-agent collaboration across four stages with timeline and project suggestions.
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·3 min
AI Agent Development Learning Roadmap: A Complete Four-Stage Guide from Beginner to Practitioner
A systematic AI Agent development learning roadmap covering core concepts, ReAct/CoT paradigms, multi-agent collaboration, and hands-on projects across four stages.
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·3 min
Learning AI Agent Development from Scratch: A Beginner's Path and Monetization Guide
A comprehensive guide to AI Agent development for beginners, covering low-code platforms, LangChain framework, and monetization strategies for building and deploying intelligent agents.
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·4 min
AI Agent Global Variable Pool & Memory Mechanisms: A Practical Guide to Workflow Node Data Passing
Deep dive into global variable pool design for AI Agent development, covering three memory types, variable scoping, node execution architecture, and placeholder variable replacement workflows.
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