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 programming tools, learn the basics, and create your first project.
Systematically master tools such as Cursor, Windsurf, and Claude Code, and understand 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 mindset for architecture 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 open the corresponding details page.
Chain + Agent + Tools + Memory, assembling LLM capabilities into applications.
Data → Index → Retrieve → Generate, feeding private knowledge to the LLM.
Use Graph + State + Edge + Checkpoint to build stateful complex 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-2026-07-10
Included 14 This is the release time of each model. Scroll below to view historical records and the official entry point.
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 labels gemini-3.5-flash as GA, Stable, positioning it as the smartest Flash model, with support for 1,048,576 input tokens and 65,536 output tokens.
Zhipu 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 documentation lists Claude Fable 5 as the strongest publicly available model, aimed at the hardest reasoning and long-horizon Agent work, with 1M context and available on major cloud platforms.
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
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.
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 historical release timelines
Meta's latest product model, designed for multimodal understanding, personal assistants, visual coding, and social content scenarios
Qwen Code's flagship model, suitable for Chinese programming, long context, 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 data07/10/2026, 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.
Macroeconomic 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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Early feedback collection · Open
You can provide feedback on course difficulty, missing case studies, and confusion about tool selection. I will prioritize real issues and incorporate them into future updates.
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.
Displayed after more authorization feedback
Real data first · Pending addition
Once the increase in feedback count is confirmed, these three lines will naturally display more real excerpts from different learners.
Wait for the first round of 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 batches.
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.
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.
Displayed after more authorization feedback
Real data first · Pending addition
Once the increase in feedback count is confirmed, these three lines will naturally display more real excerpts from different learners.
Wait for the first round of 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 batches.
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 confirmation is completed, the placeholder state here will be automatically replaced, and old feedback will not be duplicated as new feedback.
Learning questions are welcome
Early feedback collection · Open
You can provide feedback on course difficulty, missing case studies, and confusion about tool selection. I will prioritize real issues and incorporate them into future updates.
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.
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