Anthropic is offering engineers who can build large language models from scratch more than $750,000 a year. That’s a striking number, especially given how competitive AI hiring has become. The company clearly sees deep, hands-on LLM expertise as scarce and valuable. Stanford just dropped the exact CS229 lecture where they teach you the nuts and bolts of constructing these models. It runs 1 hour 44 minutes and it’s free, straight from the university’s core machine-learning course. You’ll see the math behind transformers, the training objectives, implementation details—even code snippets. Rahul highlights that this session goes farther than most in-house training at big AI firms. You’ll learn how attention mechanisms work, how to set up the training loop, what tricks prevent models from collapsing into gibberish, and how to fine-tune for tasks like summarization or question answering. If you want to understand what happens under the hood of ChatGPT or Claude, this lecture is a direct route. Grab a notebook, fire up your IDE, and follow along. You’ll pick up concepts that normally live behind closed doors in research labs.