Acknowledgments

A book about systems is itself a system, and this one had many contributors.

The technical content in this book was shaped by countless conversations with engineers and researchers working on real production systems. Several people gave detailed feedback on draft chapters, caught errors in derivations, and pointed out places where the framing did not match how the work actually gets done in practice.

A number of colleagues reviewed early drafts and offered both technical corrections and perspective on what candidates actually encounter in interviews at frontier labs. Their input made the interview framing in Part I and the end-to-end drills in Part XI significantly sharper.

The open-source research community deserves specific acknowledgment. The derivations in this book stand on the published work of the teams behind FlashAttention, the Chinchilla scaling law study, the DeepSeek architecture and training reports, the LLaMA model series, the Mixtral MoE architecture, the RLHF and DPO preference alignment papers, and the GRPO and RLVR training algorithms. Each of these is cited in the relevant chapter and listed in Appendix D. The existence of detailed technical reports from frontier labs-a relatively recent norm-made it possible to ground the book’s engineering content in actual production practice rather than academic approximations.

Finally, thank you to everyone who read early versions and offered encouragement at the moments when the project was hardest to continue. You know who you are.