Current, practical books for engineers building LLM, agent, RAG, and ML systems in production rather than just reading about AI from the sidelines.
Chip Huyen · 2024
A current O'Reilly book focused on building applications with foundation models, selected as the practical anchor for modern AI engineering.
Chip Huyen · 2022
Still one of the strongest bridges from model-building to reliable, maintainable production ML systems.
Sebastian Raschka · 2024
A hands-on route through tokenization, attention, GPT-style architecture, pretraining, and fine-tuning.
Jay Alammar, Maarten Grootendorst · 2024
Chosen for its practical, visual treatment of LLM workflows such as embeddings, classification, search, and generation.
Valliappa Lakshmanan, Hannes Hapke · 2025
A patterns-oriented O'Reilly guide for common GenAI application problems such as hallucination control, knowledge cutoffs, and customization.
Paul Iusztin, Maxime Labonne, Alex Vesa · 2024
Included for its end-to-end production LLM engineering emphasis, from data pipelines to deployment practices.
Micheal Lanham · 2025
A current agent-building pick for readers working with assistants, autonomous workflows, tool use, and multi-agent orchestration.