AI Post

🚨 Someone just open-sourced the most complete AI engineering library on the internet. It's called AI Engineering Hub. Here's what's inside: → Agentic RAG pipelines from scratch → Multi-agent systems with CrewAI, AutoGen, LangGraph → MCP server implementations (10+ real use cases) → Voice agents with real-time streaming → Fine-tuning DeepSeek with Unsloth on consumer GPUs → NotebookLM clone with RAG + citations + podcast generation → Multi-agent deep researcher that runs on Windows AND Linux → Context engineering workflows from beginner to production Here's what nobody talks about: there are 3 difficulty tiers. 22 beginner projects. 48 intermediate. 23 advanced. You can go from "what is RAG" to deploying production AI agents with persistent memory in a single repo. The projects that hit different: ClawWork-style financial agents. Paralegal crew with RAG. Stock portfolio analysis with a React frontend. A full NotebookLM clone. A reasoning model you build yourself from scratch. This isn't a tutorial collection. It's an AI engineering curriculum disguised as a GitHub repo. 100% Open Source. MIT License.