This post presents a curated reading list for AI engineers in 2025, covering around 50 essential papers, models, and blogs across various fields in AI engineering such as LLMs, benchmarks, prompting, retrieval augmented generation (RAG), agents, code generation, vision, voice, and more. The goal is to provide practical, relevant resources for those starting from scratch. The reading list is sectioned into ten fields, with each section recommending seminal papers and providing context on their significance and application.
Table of contents
Section 1: Frontier LLMsSection 2: Benchmarks and EvalsSection 3: Prompting, ICL & Chain of ThoughtSection 4: Retrieval Augmented GenerationSection 5: AgentsSection 6: Code GenerationSection 7: VisionSection 8: VoiceSection 9: Image/Video DiffusionSection 10: FinetuningHow To StartSort: