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From Algorithms to AI Systems
Data Structures and Algorithms Behind LLM Systems, in C#
This book is 4% completeLast updated on 2026-11-12
An agent running its plan is a topological sort, and a prompt cache can be a radix tree. This book works through real AI problems like these one at a time, in C# code with tests you can run.
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About
About the Book
Underneath AI systems are old, well-understood ideas like graphs, heaps, hashing, dynamic programming and concurrency. An agent running its plan is a topological sort. A prompt cache can be a radix tree with LRU eviction. Working out how many GPUs an endpoint needs is a binary search, and per-customer rate limits are token buckets.
This book takes one real AI problem at a time and works it through in C# code that runs. The topics span the main parts of an AI system, from serving models and the gateway in front of them to retrieval over documents and agents that run plans.
Each chapter starts with a small example you can follow on paper. Then it covers the design choices and what they cost, follows one request through the code, and shows how the tests check it. Every number comes from a test you can run or a source you can read.
The code is free on GitHub under the MIT license, in the AI Systems Playbook repository. The book is the guided walk through it.
The book grows chapter by chapter, with about 25 problems planned. Buy it once and you get every new chapter as it comes out.
You should be able to read C#. You don't need to know how to train a model.
Author
About the Author
Challa Ravindranath
Engineer at heart. I spent 20 years in software, at Nokia, Roche and Siemens, then a decade at Microsoft on business applications and enterprise AI. Learning has been the one constant, in the 90s, after the millennium and now in the AI era. These days I learn in public. Each week I pick one AI problem, build it in C# until I understand it properly, and share what I find so other engineers can learn from it too.
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