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25–48 of 93 · Most stars

🚀 A curated collection of AI engineering resources, roadmaps, tools, and projects covering LLMs, RAG, AI Agents, MCP, fine-tuning, evaluations, and production AI systems.

TranslatedProgrammer Yupi's (程序员鱼皮) complete AI resource collection + zero-basics Vibe Coding tutorial. Shares step-by-step OpenClaw tutorials, ways to use large models (DeepSeek / GPT / Gemini / Claude / GLM), the latest AI news, a complete collection of Prompts, an AI knowledge encyclopedia (Agent Skills / RAG / MCP / A2A), AI programming tutorials (Harness Engineering), guides to using AI tools (Cursor / Claude Code / TRAE / Codex / Copilot), AI development framework tutorials (Spring AI / LangChain), and a guide to monetizing AI products, helping you quickly master AI technology and stay at the forefront of the times. This project is the open-source documentation aiguide, which has been upgraded to the Yupi AI Navigation website (鱼皮 AI 导航网站)

A curated list of Site Reliability and Production Engineering resources.

  • site-reliability-engineering
  • production
  • availability
  • monitoring

The OWASP Mobile Application Security Testing Guide (MASTG) is a comprehensive manual for mobile app security testing and reverse engineering. It describes technical processes for verifying the OWASP Mobile Security Weakness Enumeration (MASWE) weaknesses, which are in alignment with the OWASP MASVS.

Translated✍🏻 Source Code Deep Dives, System Design & Engineering Blogs | Halfrost-Field (冰霜之地, "Land of Frost"): notes on source code analysis, system design, and engineering practice

  • ios
  • objective-c
  • swift
  • javascript

TranslatedChatGPT Chinese guide🔥, ChatGPT Chinese tuning guide, prompt guide, application development guide, curated resource list, to use ChatGPT better and make your productivity go up up up! 🚀

How to systematically secure anything: a repository about security engineering

  • security-engineering
  • security-architecture
  • secure-systems
  • threat-modeling

TranslatedOpen-source manuscript of 《深入理解 AI Infra:量化分析与系统设计》 (In-Depth Understanding of AI Infra: Quantitative Analysis and System Design), by 李博杰 (Li Bojie): starting from hardware constraints and model architecture, it quantitatively derives the system design of LLM inference and training. Includes the full text of the book, a PDF, and companion calculation tools and experiments

  • accelerator
  • ai-infra
  • ai-infrastructure
  • book