Reading List
This page is my reading list of various articles on AI and Cloud and some random notes. # Courses [LLM from scratch from Stanford](https://cs336.stanford.edu/) [LLM Inferencing at scale](https://github.com/harshuljain13/llm-inference-at-scale) # Tools, Libraries, Frameworks ## Omnigent [Omnigent AI Harness](https://omnigent.ai/) Omnigent is being used by DataBricks. Its a harness layer, which allows to multiplex models, agents. [Coding agent from scratch](https://github.com/Camrahd/claud_code) ## Graphs and Context: (https://adam-slack.medium.com/designing-context-graphs-around-how-organisations-work-part-1-79067ebbb27a) (https://adam-slack.medium.com/copying-data-into-context-graphs-part-2-27aaa5710a95) (https://adam-slack.medium.com/context-graphs-knowledge-graphs-and-agent-memory-part-0-948adfacf74b) [Fine Tuning from first principles](https://debnsuma.github.io/my-blog/posts/lora-serverless-fine-tuning/) [Usecases of search using LLM](https://blog.bytebytego.com/p/why-do...