beat-ai

Why we included this project

This one is a curated set of AI reading, updated regularly, that treats the subject as a craft to learn rather than a mystery to master. It walks from neural-network basics and how self-attention works up to large language models, and some posts get hands-on, like the series that builds a GPT from scratch on a MacBook. Recent articles lean toward the engineering layer most tutorials skip, covering agent economics and token accounting, tracing and observability for agents, and the shift from prompt engineering to context engineering. Each piece links to deeper material, so it works both as an entry point for newcomers and as a refresher for working developers who want to fill specific gaps. If you are teaching yourself AI, this is a solid supplement to a course or textbook rather than a substitute for one.