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A systematic guide to the complete learning path for AI Agent development—covering prompt engineering, RAG knowledge bases, LangChain & LangGraph, fine-tuning, and multi-agent collaboration.

A beginner-friendly guide to AI Agent development, covering the full learning path from LLM fundamentals, prompt engineering, and RAG to LangChain and multi-agent collaboration.

A complete guide to Claude Code from beginner to enterprise practice: covering CLI installation, connecting domestic LLMs via CC Switch, basic commands, Git workflow integration, automated bug fixing, and engineering capabilities like MCP and SubAgents.

Master the full DeepSeek-OCR deployment and fine-tuning workflow: vLLM inference deployment, efficient Unsloth fine-tuning, dataset preprocessing, LoRA training, validation, and RAG vector database integration.

A complete guide to learning AI Agents: from large model fundamentals and core technologies to hands-on projects. Systematically outlines beginner methods and exposes crash-course marketing traps.

Google's official hands-on: how to go from idea to production fast with AI Studio and build AI Agents using the now-GA Interactions API. The core idea—Agents are just combinations of files.

Official Google hands-on: go from idea to production fast with AI Studio, and build AI Agents with the now-GA Interactions API. The core idea: an Agent is just a composition of files—Markdown plus a few scripts, no complex Python loops needed.

A systematic guide to Claude Code, covering CLI installation, switching to domestic models, project analysis, code generation, and Git workflow. Master the CC command system and land enterprise-grade development applications quickly.

A new solo-company paradigm: replace human staff with AI Agent teams to fully automate newsletter research, writing, publishing, and analytics. 27,000 subscribers, monthly cost slashed from $1,500 to $19.

A comprehensive guide to three core AI tool types (personal assistant, CLI geek, AI IDE) in the testing era. Uncover the real challenges of AI test case generation and the new AI test development paradigm.

A complete guide to the three core categories of AI tools in the testing era (personal assistants, CLI geek tools, AI IDEs), revealing the real challenges of AI test case generation and the new AI test development paradigm.

A systematic guide to Claude Code: from CLI installation and domestic model switching to project analysis, code generation, and Git workflows. Master the CC command system and engineering collaboration.

A new one-person company model: replacing human staff with an AI Agent team to fully automate newsletter research, writing, publishing, and analytics. 27,000 subscribers, monthly cost cut from $1,500 to $19.

OpenCode has become the world's most popular open-source coding agent—8M monthly active developers, 75+ model providers, and custom sub-agent routing. This deep dive covers its core features, config tips, and business model.

A systematic guide to Claude Code's core capabilities and environment setup, covering CLI installation, switching to domestic LLMs, project analysis, Git workflow automation, and automated bug fixing to help developers get started fast.

A systematic guide to Claude Code's core capabilities and setup, covering CLI installation, switching to domestic models, project analysis, Git workflow automation, and automated bug fixing.

In the Vibe Coding era, AI coding tools are more accessible than ever. This hands-on review of Agnes Code shows how a single natural-language request generates an installable APK—no coding required. Compared with Codex and Claude Code across ease of use, closed-loop ability, and speed.

A complete beginner's guide to Claude Code: from CLI installation and switching to domestic models like DeepSeek via CC Switch, to conversational Git operations, multi-branch management, and automated bug fixing.

A complete Claude Code beginner's guide: from CLI installation and switching to Chinese models like DeepSeek via CC Switch, to conversational Git operations, multi-branch management, and automated bug fixing.

A Google DeepMind engineer reveals that over 50,000 AI agent skills come with almost no evals. This guide covers skill descriptions, test design, eval harnesses, and retirement strategies.