Start here. These give you the mental models and practical frameworks.
| Book | Author(s) | Year | Why It Matters |
|---|
| Co-Intelligence: Living and Working with AI | Ethan Mollick | 2024 | NYT bestseller. Best starting point for understanding AI as a thinking partner. Introduces “centaur vs cyborg” framework. |
| AI Engineering | Chip Huyen | 2025 | The definitive systems-design book. Deployment, monitoring, CI/CD for ML, data pipelines. |
| The LLM Engineering Handbook | Paul Iusztin, Maxime Labonne | 2025 | Operations manual: prompt engineering, fine-tuning, RAG, evaluation, production patterns. |
For when you want to understand how things actually work under the hood.
| Book | Author(s) | Year | Why It Matters |
|---|
| Hands-On Large Language Models | Jay Alammar, Maarten Grootendorst | 2024 | Build-and-fine-tune approach using Hugging Face, LangChain. Learn by doing. |
| Build a Large Language Model (from Scratch) | Sebastian Raschka | 2024 | Builds a transformer from scratch in PyTorch. Deep understanding of LLM internals. |
| Building LLMs for Production | Louis-Francois Bouchard, Louie Peters | 2024 | Latency, cost optimization, observability, deployment architecture. |
| Book | Author(s) | Year | Why It Matters |
|---|
| Prompt Engineering for LLMs | John Berryman, Albert Ziegler | 2024 | Few-shot, chain-of-thought, prompt patterns. Covers Claude and other models. |
| Prompt Engineering for Generative AI | James Phoenix, Mike Taylor | 2024 | Written by GitHub Copilot architects. Text, image, and code generation strategies. |
| Book | Author(s) | Year | Why It Matters |
|---|
| Building Agentic AI Systems | Anjanava Biswas, Wrick Talukdar | 2025 | Autonomous agents, reasoning, planning. Auto-GPT, BabyAGI, LangGraph patterns. |
| Designing Machine Learning Systems | Chip Huyen | 2022 | Foundational. ML systems design under real-world constraints. |