Books Most LLM books teach you to use models. This one teaches you to build them — every layer, every optimizer step, every cache, every quantization scheme — and then to deliberately break each piece so you understand why it exists in the first place.
Welcome to the Leanpub Launch video for Under The Hood: Build Every Layer of a Large Language Model from Scratch by Ramchand Kumaresan!
About the Book #
Most LLM books teach you to use models. This one teaches you to build them — every layer, every optimizer step, every cache, every quantization scheme — and then to deliberately break each piece so you understand why it exists in the first place.
It is a workshop in book form. 35 hands-on projects, ~250,000 words, one tight spiral that takes you from a single autograd scalar all the way to fusing independently trained specialists into a routed system. No black boxes. No "import library, call method." You write the code, you run it, you break it, you measure what broke.
Each project follows the same disciplined rhythm: Hook → The Concept → Why It Matters → The Build → BREAK IT → Optional Homework → Questions To Answer → Go Further → What You Now Know. Reading the book without breaking the code is half the experience. The breaks are where the lessons actually live.
A public code companion lives at github.com/mechramc/Under-the-hood with runnable build.py, tests, and captured outputs for every project.
If you have ever read a transformer paper and felt that the diagram and the code were in two different universes — this book closes that gap. Build it. Break it. Measure it.
About the Author #
Ramchand Kumaresan is a Senior Program Manager at Procore Technologies and the founder of Murai Labs, a small AI research lab he runs solo from outside Austin. His arXiv work includes KALAVAI, UYIR, and Orion. He started writing this book because he kept meeting engineers who could ship against the OpenAI API but couldn't explain a logit — and realized he was one of them. Eighteen months later, this is the book he wished he'd had.