# Azure OpenAI + LLM

A curated, regularly updated collection of resources on Azure OpenAI and large language models, covering RAG, agents, prompt engineering, and LLMOps, organized by topic and by publication date.

Azure OpenAI + LLM is a curated collection of resources about Azure OpenAI, large language models, and their applications. Each entry is briefly summarized and dated by first commit or publication so readers can track how the field has moved.

The list is organized around three eras: parametric knowledge from pretraining and fine-tuning, context-time techniques such as prompting and retrieval-augmented generation, and agentic engineering topics like harness design, tool use, multi-agent orchestration, and the Model Context Protocol. Sections cover RAG systems, agent frameworks, evaluation, safety and security, and learning resources.

The collection is updated monthly, with candidate additions tracked in an issue before each update.

Website: https://github.com/kimtth/azure-openai-llm-notes