Only by understanding the mechanism can you master the tool. From beginner fundamentals to enterprise-level practice, systematically master mainstream AI coding tools such as Cursor, Copilot, and Claude Code.
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Getting started → engineering implementation → monetization at scale, three tracks at a glance
Never written code? No problem. Understand AI coding tools, master the basics, and create your first project.
The system is familiar with tools such as Cursor, Windsurf, and Claude Code, and understands the core technologies of MCP, Skill, and Agent.
Gain a deep understanding of the principles and advanced features of AI coding tools, and master enterprise practices and architectural trade-off thinking.
Understand architectures such as Transformer, Mamba, MoE, and RAG, and master the thinking behind architectural selection.
Master AI programming tools through real projects and build end-to-end practical experience from requirements to delivery.
An enterprise AI team-building guide for organizing AI teams, establishing workflows, and building a learning organization.
Turn your capabilities into a system that is deliverable, repeatable, and compounding: positioning → productization → automation → growth → review.
Understand the division of labor and collaboration of mainstream AI frameworks at a glance
Each framework comes with a high-resolution infographic + Code Map + code examples; click to enter the corresponding detailed page.
Chain + Agent + Tools + Memory, assembling LLM capabilities into applications.
Data → Index → Retrieve → Generate, feeding private knowledge to the LLM.
Graph + State + Edge + Checkpoint, build complex stateful workflows.
Goal → Plan → Execute → Reflect, let the AI do the work itself.
Multi-Agent + SOP, the AI team divides tasks according to the process to complete the project.
View the comparison table of the five major frameworks, the selection guide, and the complete Code Map overview.
Automatically try to read the latest model data, prioritizing the wording from the official model page/API docs; if the interface is unavailable, clearly fall back to the static seed and do not treat unverified content as up to date.
When the page is opened, it is requested first /api/models; clicking "Request latest" triggers once /api/models/refresh。
This page has loaded static validation fallback data from the online API; it will switch to real-time updates after you configure an external search key.seed-official-verified-2026-07-20
Included 15 This is the release time of each model. Scroll below to view historical records and the official entry point.
xAI released Grok 4.5 as a frontier model for coding, agentic tasks, and knowledge work. It offers a 500K context window, configurable reasoning effort, and native tool calling.
OpenAI has launched the GPT-5.6 series: Sol is for frontier capabilities, Terra balances intelligence and cost, and Luna is designed for high throughput; the gpt-5.6 alias points to Sol.
Kimi API documentation announcement K2.7 Code has been officially released, and the high-speed version is now available simultaneously. Supports 256K context, long thinking, text/image/video input, and tool calls.
Google Docs marks gemini-3.5-flash as GA, Stable, positioning it as the smartest Flash model, supporting 1,048,576 input tokens and 65,536 output tokens.
Zhipu has released GLM-5.2, supporting 1M lossless context and enhancing coding, long-horizon tasks, complex systems engineering, deep debugging, and project-level context handling.
Anthropic's most powerful public model, for the most demanding reasoning and long-horizon agent work
OpenAI flagship for complex reasoning and coding listed on the official model page
xAI describes it as its smartest and fastest model yet, built for coding, agents, and knowledge work
GA stable model, described in Google docs as the smartest Flash model
Prefer the official release date; items that cannot be officially verified are marked as directory listing time.
xAI’s frontier flagship released on July 16, 2026, suited to coding, agentic tasks, complex reasoning, and knowledge work
A cutting-edge flagship released by OpenAI on 2026-07-09, suitable for complex software engineering, Agents, and domain expertise work
Kimi's latest coding model, designed for long-context code tasks, multimodal tool calls, and high-success-rate Agentic Coding
Google Gemini 3.5 stable flagship model, suitable for large-scale Agents, coding loops, multimodal, and long-horizon workflows
Zhipu 2026-06 flagship, suitable for Chinese engineering scenarios, long-horizon agents, complex system development, and domestic compliance selection
Anthropic's highest-capability public model at the 2026-06-09 GA, suitable for complex software engineering, deep research, and highly autonomous agents
xAI’s current flagship general-purpose model, suitable for tool calling, analysis, long-context, and production-grade Agent workflows
xAI's fast model for coding agents, suited for prototyping, lightweight code tasks, and low-latency engineering workflows
DeepSeek V4 lightweight, budget-friendly model, suitable for cost-sensitive long-context and everyday tasks
DeepSeek V4 preview flagship, focusing on open source, long context, and Agentic Coding
OpenAI flagship model before the release of GPT-5.6, retained in the historical release timeline
Meta's latest product model, designed for multimodal understanding, personal assistants, visual coding, and social content scenarios
Qwen Code flagship model, suitable for Chinese programming, long-context tasks, and everyday Agent development
OpenAI's mini model for high-frequency engineering tasks, suitable for cost-sensitive code, sub-agents, and tool-calling scenarios
Google's lightweight and stable model for large-scale calls, suitable for translation, extraction, transcription, and high-frequency cost-sensitive tasks
IDE / web / CLI / design tools + mainstream large models · model data07/20/2026, 08:00· SourceStatic seed
AI-first IDE, supports Skill/Agent/MCP
Terminal-integrated AI assistant, the MCP ecosystem is the most active
Generate UI with natural language, Figma integration
Fast Context technology, 1M token context
AI pair programming in terminal, Git native
Collaborative UI design tools enhanced with AI features
8 1 curated in-depth project · 4 Trending entries · 4 high-Star direction searches; on the homepage, first look at the thumbnails, then go to the detailsGitHub Trending。
ECC code optimization giant
Ultra-large-scale agents/rules/skills/hook system: performance optimization, rule binding, security review, and continuous evolution.
Highly disciplined AI programming engineering OS
A strict process upgrades AI from a “typist” to an “engineer/architect”: TDD, division of labor, acceptance.
Organized anthropomorphic enterprise team
Move the “organization” into the repository: a large number of role templates with metrics and deliverables, collaborating by department.
GSD anti-context-corruption system
Engineering countermeasures against Context Rot: planning → wave-based isolated execution → acceptance → atomic commit.
Minimalist Entrepreneur skill library
The 10 startup companion skills from "The Minimalist Entrepreneur": prioritize validation, and oppose building first and selling later.
Macro-environment financial trading agent
Multi-agent collaboration + debate/reflection + risk-control closed loop to make more robust trading decisions.
Top tech blogs, AI podcasts, industry reports, newsletters, developer communities, and high-quality courses, with commonly used links curated by category.
OpenAI / Anthropic / Google / Meta / Vercel
Latent Space / Practical AI / Lex Fridman
State of AI / Stanford AI Index / McKinsey / Gartner
The Batch / Import AI / AI Snake Oil
Hacker News / r/MachineLearning / Discord
fast.ai / Karpathy / 3Blue1Brown / Coursera
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Do not disclose private information
Anonymized display · Long-term rules
Only summaries are displayed in the showcase area; do not display email addresses, phone numbers, company names, project names, or other information that may identify a person.
Feedback will be added to the update list
Actual project progress · Continuous processing
Confirmed issues are turned into course improvement items, rather than fake reviews that look flashy but cannot be tracked.
Show after more authorization feedback
Real data first · Waiting to be added
Once the increase in feedback count is confirmed, these three lines will naturally display more real excerpts from different learners.
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After receiving real email feedback with explicit authorization, I will first anonymize and organize it, then display it here in rotation.
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The original content in the email will not be made public directly. Only after you check authorization and complete anonymization processing will it appear here.
Feedback will be sorted manually first
Real feedback wall · Ongoing call for submissions
I will keep the real issues and suggestions from the feedback, but remove personal information such as email addresses, company names, and project details.
Feedback will be added to the update list
Actual project progress · Continuous processing
Confirmed issues are turned into course improvement items, rather than fake reviews that look flashy but cannot be tracked.
Show after more authorization feedback
Real data first · Waiting to be added
Once the increase in feedback count is confirmed, these three lines will naturally display more real excerpts from different learners.
Waiting for the first approval feedback
Email feedback wanted · Now accepting submissions continuously
After receiving real email feedback with explicit authorization, I will first anonymize and organize it, then display it here in rotation.
Public display requires authorization
Privacy first · Waiting for authorization
The original content in the email will not be made public directly. Only after you check authorization and complete anonymization processing will it appear here.
Feedback will be sorted manually first
Real feedback wall · Ongoing call for submissions
I will keep the real issues and suggestions from the feedback, but remove personal information such as email addresses, company names, and project details.
Wait for the next real feedback
Feedback wall supplement · Automatic updates
After the new email feedback is confirmed, the placeholder status here will be automatically replaced, and old feedback will not be duplicated and treated as new feedback.
Learning questions are welcome
Early feedback collection · Open
You can share feedback on course difficulty, gaps in the case studies, and confusion about tool selection. I will prioritize organizing real issues into future updates.
Do not disclose private information
Anonymized display · Long-term rules
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