Kanwal Mehreen Recommends 7 Free Books for Production AI Systems
Updated
Updated · KDnuggets · Nov 12
Kanwal Mehreen Recommends 7 Free Books for Production AI Systems
1 articles · Updated · KDnuggets · Nov 12
Summary
Seven free books are Mehreen’s picks for engineers moving from quick AI demos to production systems that can handle heavy traffic without becoming too slow or too expensive.
The list centers on practical bottlenecks beyond model accuracy—latency, GPU memory, deployment, context management, observability, security and inference cost—especially for AI agents and LLM applications.
Chip Huyen’s Machine Learning Systems Design opens the list with 4 end-to-end stages and 27 design questions, while Stas Bekman’s open reference draws on projects including BLOOM-176B and IDEFICS-80B.
Several newer titles focus on agent and inference engineering, covering RAG, tool use, batching, quantization, distributed training and serving across thousands of accelerators, with LLaMA 3 used as a practical example.
Mehreen argues that as coding agents make AI apps easier to build, systems engineering is what separates a working prototype from a reliable, fast, secure and affordable product.
If AI prototyping is so easy, why do so many production systems collapse under real-world memory pressure and GPU limits?
Will managed cloud services eventually abstract away complex AI bottlenecks, or is deep systems knowledge now permanently required for developers?
How do hidden semantic failures in generative models prove that traditional software observability is completely inadequate for modern AI applications?