Practical tutorials and guides for AI beginners. No jargon, just step-by-step instructions.
What is AI, how does it work, and what you need to know first.
A practical AI learning guide from a creator who's been through it — 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 — LLM (brain), Prompt (command), Agent (employee), Codex (coding specialist), Skill (SOP), Workflow (step sequence), API (connector), and Knowledge Base (filter) — explained through everyday analogies a beginner can grasp in one sitting.
A complete journey through 12 AI concepts — Token, Prompt Engineering, RAG, Tool Calling, MCP, Context Engineering, Skill, Computer Use, Agent, Harness Engineering, Workflow, and Workspace Agent — with code snippets and actionable tips for each.
A beginner-friendly guide to the 3-layer AI pyramid — LLM (brain), Multimodal (senses), Tools & Agents (skeleton) — plus how to build your own AI agent with Kouzi (Coze), no coding required.
Step-by-step guides for ChatGPT, Claude, Midjourney and more.
Build an auto-evolving AI knowledge base that collects, filters, and structures new information on its own. Master the closed-loop workflow — folder-trigger collection, JSON knowledge-sorting agent, API write-back with duplicate skip, and scheduled self-optimization — so your knowledge base grows without manual file uploading.
A step-by-step guide to building an AI second brain with WorkBuddy + IMA Knowledge Base. Master three core steps — Connect (authorize and import documents), Use (the 'Based on IMA Knowledge Base' prefix for hallucination-free answers), and Update (keep your knowledge fresh) — plus the advanced bidirectional closed-loop workflow powered by the IMA OpenAPI that auto-saves AI output back into your knowledge base.
Over 18 days, 400 tasks, and 71 billion tokens — 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 — installation (quick try + permanent + headless + source build), API key setup, the four working modes, permission levels, plugin management, and creating your first plugin.
AI for resumes, presentations, scripts, and real-world tasks.
A practical guide to AI-powered spreadsheet creation — 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 — WorkBuddy (AI entry), Business Skills (capability encapsulation), and Existing Systems (Cordys CRM) — 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.
ChatGPT vs Claude, Midjourney vs DALL-E — honest side-by-side tests.
An Agent Harness is the work environment for your AI model, and there is no universal best — only the right fit. This decision guide compares the three leading engineering forms: DeepSeek Harness (full runtime control, everything is a plugin), OpenCode (ready-to-use with extensibility), and Pi (a minimal 4-tool kernel under 1,000 tokens for ~3x context reduction and 50%+ cost savings) — covering core design, key features, install commands, and a concrete how-to-choose framework for your AI workflow.
80% of teams pick ReAct or Multi-Agent just because those are the only two they've heard of. This decision guide builds a coordinate system for choosing among 7 mainstream agent architectures — Single Agent, ReAct, Plan and Execute, Multi-Agent, Route + Skill, Blackboard, and Graph Workflow — covering the pros, cons, and fit of each, plus the full evolution line from lightweight to enterprise-grade.
A comprehensive toolkit guide across 9 domains — text, image, video, audio, digital humans, browsers, coding, knowledge bases, and agents — with top picks, free alternatives, and open-source options for each category.
A comprehensive guide covering 12 scenarios — 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) — with free alternatives for every category.
New models, major updates, and what they actually mean for you.
Hands-on testing of DeepSeek V4 Pro 0813 with two real projects — a 6-style personal blog built in 25 minutes and a runnable 3D racing game in 40 minutes — showing delivery capability beyond benchmark scores.
Feishu's three groundbreaking AI features — 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 — plus the OpenClaw open-source plugin for multi-model integration.
DeepSeek V4 Flash official launch breakdown — 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 — 9 Chinese models in top 25, with GLM 5.2 at #4 — plus a Python test script and model selection guide for developers.
In-depth reviews, comparisons, and guides for the best AI tools.
A hands-on guide to ByteDance's Seedance 2.5 video model — 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 — 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 — Codex (5/5), WorkBuddy (4/5), Trae & Z-Code (3.5/5), Claude Code (2.5/5), OpenClaw/Hermes (2/5) — with setup steps, pros/cons, and a decision guide based on network/payment accessibility.
A beginner-friendly guide to OpenSpec — a lightweight specification-driven development (SDD) framework that structures AI coding projects through a 4-step workflow (Explore → Generate Docs → Develop → Archive), comparing it with Spec-Kit and Superpowers for different project scales.
Deep dives into AI concepts, architectures, and how models actually work.
Vibe-coding AI often cuts corners — 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 — energy (solar/wind/nuclear), chips (ASML lithography, semiconductor manufacturing), PCB & MLCC, large models (training pipeline), and smart robots — plus investment, career, and skill-building opportunities in each layer.
A practical guide to effective AI collaboration using a 3-step framework — 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) — embracing 'learning by doing' over 'learn first, use later.'
A deep dive into why most AI knowledge bases fail — 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.