ai-engineer-notebooks teaches agents and RAG from raw API calls, deliberately refusing LangChain.

440 stars, created August 11, covering 12 sections from model APIs through structured output, RAG, evals, agent loops, LoRA versus fine-tuning, security, LLMOps and serving, plus three case studies and a capstone (GitHub). The stance is that you write the agent loop, RAG and evals from raw API calls first so you understand what the frameworks do before reaching for them. Everything runs on the free Groq tier with no credit card, GPU sections on Colab's free T4. MIT.