@ai.data.tech: A curated roadmap of essential books for AI engineers covering production systems, multi-agent frameworks, system reliability, custom stacks, practical LLM application development, and business strategy. AI Engineering: Building Applications with Foundation Models by Chip Huyen – For understanding production-ready AI. 30 Agents Every AI Engineer Must Build by Imran Ahmed, PhD – To go from individual tools to full multi-agent systems. Designing Machine Learning Systems by Chip Huyen – To learn why ML systems fail after shipping and how to build reliable production applications. Learn Mistral by Pavel Charhashin – To learn beyond the default AI tech stack. LLM Engineer’s Handbook – For hands-on, real-world LLM application building. Becoming Native AI by Nate Herk – To transition from building tools to delivering business outcomes and consulting. #AIEngineering #MachineLearning #LLM #AIAgents #DataScience #SoftwareEngineering
