A practical AI learning guide from a creator who's been through it β start with a specific problem, learn AI terminology like a baby, learn by doing, and find the right resources without information overload.
A jargon-free introduction to 8 core AI concepts β LLM (brain), Prompt (command), Agent (employee), Codex (coding specialist), Skill (SOP), Workflow (step sequence), API (connector), and Knowledge Base (filter) β explained through everyday analogies a beginner can grasp in one sitting.
A beginner-friendly guide to the 3-layer AI pyramid β LLM (brain), Multimodal (senses), Tools & Agents (skeleton) β plus how to build your own AI agent with Kouzi (Coze), no coding required.
Over 18 days, 400 tasks, and 71 billion tokens β how to move Codex from basic chat-box demos to reliable production tooling. Five levels: direct submission, document-driven workflows, Git code management, open source ecosystem integration, and multi-agent collaboration.
A complete beginner's guide to DeepSeek Harness β installation (quick try + permanent + headless + source build), API key setup, the four working modes, permission levels, plugin management, and creating your first plugin.
OpenCode Desktop is an open-source AI coding agent (197K+ GitHub stars) that works directly in China with built-in free models. A beginner's guide to installation, Build vs Plan modes, @ / ! commands, and free-model usage rules.
A practical guide to AI-powered spreadsheet creation β from choosing AI tools and providing profession-specific requirements, to advanced use cases like e-commerce operation tables, expense report processing, and data visualization with interactive charts.
A practical enterprise AI transformation blueprint using a three-layer architecture β WorkBuddy (AI entry), Business Skills (capability encapsulation), and Existing Systems (Cordys CRM) β with detailed Skill file anatomy, import process, and web/mobile demonstrations.
A comprehensive guide to launching AI-powered WeChat Mini Programs, covering essential tools, category selection, code upload, user authentication, ICP filing, and common pitfalls.
Build a fully functional investment research dashboard with Claude Code in minutes. Pull real-time stock data, calculate financial metrics, and visualize trends for large-cap stocks.
A comprehensive toolkit guide across 9 domains β text, image, video, audio, digital humans, browsers, coding, knowledge bases, and agents β with top picks, free alternatives, and open-source options for each category.
A comprehensive guide covering 12 scenarios β from deep research (Gemini 3.1 Pro), writing (Claude Opus 4.6), coding (Cursor/Claude Code/Codex), image gen (Nano Banana Pro), video (Seedance 2.0), to AI agents (Genspark) β with free alternatives for every category.
Rigorous benchmark of GLM-5.2 vs GPT-5.5 and Claude Opus 4.8 across authentication migration and web full-stack projects β plus sentiment analysis of 6,690 community comments revealing why developers both love and hate it.
Hands-on benchmark of MiniMax M3 β the first open-source model combining native multimodality, million-token context, and agent capabilities β tested across 5 scenarios including 3D maze, pocket watch animation, keyframe extraction, and custom computer-use agents.
Hands-on testing of DeepSeek V4 Pro 0813 with two real projects β a 6-style personal blog built in 25 minutes and a runnable 3D racing game in 40 minutes β showing delivery capability beyond benchmark scores.
Feishu's three groundbreaking AI features β one-click personal AI Agent (Little Lobster), Feishu Miaoda generating $20K business systems for $100 in natural language, and Multidimensional Table Agent with auto table/dashboard/permission generation β plus the OpenClaw open-source plugin for multi-model integration.
DeepSeek V4 Flash official launch breakdown β 82.7 Terminal-Bench (global 2nd), 36-107x cheaper than GPT-5.6 Sol at $0.14/M input tokens, 284B MoE architecture with 13B active per token, 1M native context, plus Python API setup, agent task execution, and cost optimization tips.
Week 29 front-end coding benchmark results: Kimi K3 debuts at #1 globally (1679 score), surpassing Claude Fable-5 and GPT-5.6 Sol β 9 Chinese models in top 25, with GLM 5.2 at #4 β plus a Python test script and model selection guide for developers.
A hands-on guide to ByteDance's Seedance 2.5 video model β direct 30-second commercial video generation, smart editing, style replication, multi-language localization, and cost control strategies. Zero-basics to professional in one workflow.
A beginner-friendly guide to Douyin's AI Creation Agent powered by Seedream 5.0 Pro and Seedance 2.0 β conversational image and video generation without complex prompts, featuring reference photo upload, iterative refinement, trend-based creation, and one-click remixing of existing AI videos.
A practical ranking of 6 AI Agent tools for Chinese beginners β Codex (5/5), WorkBuddy (4/5), Trae & Z-Code (3.5/5), Claude Code (2.5/5), OpenClaw/Hermes (2/5) β with setup steps, pros/cons, and a decision guide based on network/payment accessibility.
A beginner-friendly guide to OpenSpec β a lightweight specification-driven development (SDD) framework that structures AI coding projects through a 4-step workflow (Explore β Generate Docs β Develop β Archive), comparing it with Spec-Kit and Superpowers for different project scales.
Vibe-coding AI often cuts corners β placeholder comments, empty stubs, mock data, and skipped logic that looks complete but can't run. Practical prompt constraints, a reusable self-check snippet, and a manual validation workflow to catch unfinished code before it wastes your debugging time.
A bottom-up overview of the AI industry chain β energy (solar/wind/nuclear), chips (ASML lithography, semiconductor manufacturing), PCB & MLCC, large models (training pipeline), and smart robots β plus investment, career, and skill-building opportunities in each layer.
A practical guide to effective AI collaboration using a 3-step framework β Put It Forward (start with real tasks, not tutorials), Explain It Clearly (break vague feelings into specific parameters), and Keep Asking (build a two-way question loop) β embracing 'learning by doing' over 'learn first, use later.'
Β·5 min read
AI CollaborationPrompt EngineeringLearning by Doing
A deep dive into why most AI knowledge bases fail β covering RAG fundamentals, ingestion pipeline (cleaning, semantic chunking, vectorization), QA pipeline (question understanding, reranking, context assembly), four-layer implementation, hybrid retrieval, and practical lessons from real enterprise projects.