#ChatGPT source selection
383 related articles
·4 min
Claude Code Getting Started Guide: Core Advantages and Selection Recommendations for AI Coding Assistants
Claude Code is Anthropic's local AI coding assistant featuring full project context, auto error correction, and high-accuracy code generation. Compare it with Cursor, Trae, and Codex.
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·6 min
Codex China Direct Access Tutorial: Guide to Using DeepSeek as a ChatGPT Replacement
Use Codex without a ChatGPT account! This guide explains a China direct access solution for integrating the DeepSeek API via the Codex++ management tool.
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·7 min
The Complete Codex Guide: From Installation to Real-World Practice
Master OpenAI Codex fast, even from scratch! Learn Codex vs ChatGPT differences, four versions, interface tips, plugins & skills, browser automation, plus six best practices.
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·7 min
Otari: A Comprehensive Look at the Open-Source LLM Control Plane Tool
An in-depth analysis of the open-source LLM control plane tool Otari—covering unified multi-model access, cost observability, and security compliance governance to help teams build manageable, production-grade AI infrastructure.
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·6 min
Does AI Adoption Actually Lead to More Hiring? Explaining This Counterintuitive Phenomenon
Growing data shows companies aggressively adopting AI are actually hiring more. This article explores the overlooked complex relationship between AI and employment through the Jevons Paradox, new job creation, and competitive divergence.
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The Complete Guide to Local LLM Deploy…
·2 min
The Complete Guide to Local LLM Deployment: Tools, Hardware, and Model Selection
A complete guide to locally deploying open-source LLMs: covering VRAM requirements, quantization, tools like Ollama and LM Studio, and model selection tips for Llama, Qwen, and more.
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·7 min
The Complete Guide to OpenCode: Installing, Configuring, and Using the Terminal AI Coding Assistant
An in-depth guide to installing, configuring, and extending OpenCode, the terminal AI coding assistant. Covers desktop and WSL installation, model config, MCP integration, and custom Agents.
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·6 min
LangChain 1.0 Comprehensive Guide: Three Core Frameworks and Hands-On AI Application Development
Deep dive into LangChain 1.0's architecture: LangChain framework, LangGraph multi-Agent orchestration, and LangSmith observability platform, with hands-on RAG and intelligent customer service projects.
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·6 min
Step-by-Step Guide: Power Codex with DeepSeek for Users Without ChatGPT Access
No ChatGPT account? No problem! Learn how to power Codex with DeepSeek API using the Codex++ management tool. Five easy steps, starting at just $1.40.
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·2 min
Claude Code Deep Dive: Why It's the Most Powerful AI Coding Tool
A deep dive into Claude Code's core strengths: agentic coding, full project context, and auto-debugging — compared against Cursor, Trae, and Codex to help developers choose the best AI coding tool.
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·3 min
Local AI Agent in Action: Auto-Record World Cup Highlights and Stop Staying Up to Watch Soccer
A hands-on test of the AiKanQiu Agent on Flowin AIPC: auto-schedule, record, and extract World Cup highlights locally — no more staying up all night for soccer.
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·4 min
AI-Powered Chrome Extension Monetization: A No-Code Practical Guide
No coding skills? Learn how to build Chrome extensions for global markets using AI — from finding demand and generating code to publishing on the Chrome Store and earning subscription revenue.
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·3 min
A Practical Guide for Chinese Users: Powering Codex with DeepSeek
No ChatGPT account? Learn how to configure DeepSeek as Codex's underlying model using the Codex++ Manager tool — a practical guide for users in China.
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·3 min
UE5.8 + Claude Code: MCP Plugin Configuration and Hands-On Tutorial
Complete guide to configuring UE5.8's native MCP plugin: enable core plugins, install Claude Code, set environment variables, generate config files, and connect AI agents to Blueprints, PCG, and materials.
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·3 min
Exposing the 'Claude Fable 5' Scam: A Guide to Identifying Fake AI Products
"Claude Fable 5" doesn't exist. This guide exposes the AI scam's core red flags: fake version numbers, fabricated demos, "no-VPN China access" lies, and traffic funnel tactics.
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·7 min
AI Agent Development: A Four-Stage Competency Model from 15K to 40K RMB Salary Growth Path
A detailed four-stage competency model for AI Agent development: from Python/RAG basics (15K) to workflow orchestration (20K), inference optimization (30K), and Agent cluster governance (40K RMB).
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·7 min
Agent Loop Explained: The Core Runtime Mechanism and Think-Act Cycle of AI Agents
Deep dive into Agent Loop mechanics: the think-act cycle, how agents differ from LLMs, termination conditions, and design principles for building autonomous AI Agent systems.
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·3 min
Dify Comprehensive Guide: The Open-Source Platform for Building AI Apps Without Code
Deep dive into Dify, the open-source LLM app development platform featuring visual workflow engine, RAG knowledge base, Agent capabilities, hundreds of model integrations, Docker deployment, and comparisons with LangChain, Coze, and FastGPT.
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·4 min
LangGraph.js Practical Guide: A Frontend Engineer's Path to AI Agent Development
A practical LangGraph.js guide for frontend engineers covering LangGraph vs LangChain comparison, workflow vs general-purpose agent types, and layered Agent architecture design.
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·4 min
The Four Stages of AI Engineering Evolution: From Prompt to Loop Engineering Explained
A systematic breakdown of the four stages of AI engineering: Prompt Engineering, Context Engineering, Runtime Environment Engineering, and Loop Engineering — with core logic, bottlenecks, and real-world use cases.
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