Eureka Labs is Andrej Karpathy's attempt to answer a question he is unusually qualified to ask, which is what teaching should look like when the teacher is an AI native system designed around the best human instructor rather than a lecture hall. The flagship is LLM101n, a course whose goal is that you build your own small language model from the ground up, starting with the tokenizer and the raw mechanics of attention and ending with a model you can actually chat with. If you have watched his Zero to Hero series or worked through nanoGPT, you already know why this matters, because nobody explains the internals of these models with more clarity, and the whole philosophy is that you do not understand something until you have built it yourself. The material that has been released so far lives up to that reputation, the code is clean and readable, the explanations are patient, and the sequencing takes you from first principles to working artefacts in a way that very little else in this space attempts.
The honest problem is timing. This is a course being written and released in public, in stages, and at the moment a good deal of it is still a promise rather than a lesson you can sit down and complete. There is no reliable schedule, most people will not have access to a live cohort, and there is nothing resembling a certificate, so what you are getting is a set of superb building blocks rather than a finished, hand held journey. It is also unapologetically technical, you need real Python and enough comfort with the underlying maths to follow a derivation, so it sits alongside his other work as material for people who want to genuinely understand these systems rather than beginners looking for a gentle tour.
My honest view is that the ceiling here is as high as anything in AI education, and I would rather learn to build a language model from Karpathy than from almost anyone alive, but I would set expectations carefully. Treat it as an extraordinary work in progress worth following closely, pair the released parts with his existing videos to fill the gaps, and be ready to come back as more of it lands, because the finished version could genuinely be the best of its kind.