@nini_incrypto_: Want to learn AI system design? Just look at the real-world experience of top-tier companies! This amazing repository on GitHub aggregates over 500 real GenAI deployment cases from more than 130 big companies. It doesn't teach basic textbook theory but specifically breaks down the technical decisions of top teams in real production environments: 1. Uber: …
Summary
A repository on GitHub aggregates over 500 real GenAI deployment cases from more than 130 big companies, breaking down top teams' technical decisions in production environments, such as Uber's real-time traffic scheduling across multiple model providers.
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@wsl8297: When learning AI, the scariest part is getting stuck at "understanding the theory" and freezing when it's time to write code — not knowing where to start, and unable to find decent practice projects. I unearthed a practical treasure trove on GitHub: AI-Project-Gallery. It collects 30+ high-quality AI projects, covering classic topics like house price prediction and disease classification, as well as hot applications like Gemini chatbot and document generator...
This post shares a curated GitHub repository containing over 30 practical AI projects, covering domains from regression to generative AI, with many end-to-end examples, suitable for learners and developers.
@nuannuan_share: If I wanted to land a $200K AI engineer job in 90 days, I wouldn't go back to school. I'd master these 10 GitHub repositories. 1. awesome-llm-apps — A production-grade AI guide covering RAG, agents, and multimodal apps with full code. 106K+ stars. Repo …
A Chinese social media post recommends 10 GitHub repositories, claiming that mastering them can help land a $200K AI engineer job within 90 days. The repos cover mainstream AI development frameworks and tools including LangChain, LangGraph, CrewAI, Ollama, and Qdrant.
@IndieDevHailey: This might be the hardest-core open-source AI engineering course on the internet. The GitHub trending project: ai-engineering-from-scratch has already gained 17.4k+ Stars. It's not another AI tutorial that teaches you how to call APIs; instead, it truly guides you to build AI systems from scratch.
Introduces the trending open-source AI engineering course project ai-engineering-from-scratch on GitHub, which has earned 17.4k+ Stars. It offers 435 lessons across 20 stages, covering mathematical principles to hand-built AI systems, supports multiple languages, and aims to help learners deeply understand the underlying principles of AI.
@GitHub_Daily: Using AI agents for production-grade tasks—writing code, running workflows, calling APIs—works fine initially, but as the scale grows, things easily get out of control: permissions too broad, context loss, and debugging becomes impossible. That's where agents-best-practices comes in: a complete guide to designing a runtime framework for AI agents, not limited to coding scenarios, but also applicable to operations, sales...
Introduces the agents-best-practices repository, a production-grade AI agent runtime framework design guide covering tool permission tiers, context compression, etc., supporting Codex and Claude Code installation.
@edwordkaru: Those Twitter 'gurus' charging hundreds of dollars to teach AI Agent building are about to be exposed. Today I came across a hardcore project on GitHub that's topping the charts: ai-engineering-from-scratch. No exaggeration — this thing obliterates all those paid scams, 40…
A comprehensive, open-source AI engineering curriculum with 435 lessons across 20 phases, covering everything from linear algebra to multi-agent systems, available for free on GitHub.