"Building LLM Powered Applications" — A practical guide to LLM application development"Generative AI with LangChain" — In-depth guide to the LangChain framework"Designing Autonomous AI Agent Systems" — Principles of Agent system design
DeepLearning.AI "Building Agentic RAG with LlamaIndex" seriesLangChain Academy — Official LangChain courses (free)Andrew Ng "AI Agentic Design Patterns" series
Project Description
LangChain Most popular Agent development framework LangGraph Stateful Agent workflows CrewAI Multi-Agent role-playing framework AutoGen Microsoft multi-Agent framework (0.4 event-driven architecture) Dify Open-source LLM application platform mem0 Agent memory layer ChromaDB Lightweight vector database
LangChain Discord — Active developer communityReddit r/LangChain — Discussion and sharingGitHub Discussions — Official discussion boards for each frameworkHugging Face — Open-source model community
Juejin (稀土掘金) — Search "Agent开发", "LangChain实战" for many Chinese practice articlesZhihu (知乎) — Follow "AI Agent", "LLM应用开发" topics for industry discussions and technical analysisCSDN — Agent development tutorials and troubleshooting recordsBilibili / YouTube Chinese channels — Search "Agent开发教程" for quality video tutorialsWeChat Official Accounts — Recommended: 机器之心, 量子位, AI科技大本营 (track latest Agent technology trends)Tongyi Qianwen Community — Alibaba Cloud's LLM developer community, suitable for developers using domestic models
The following are core academic papers referenced in this book, organized by technical topic. Each topic has a corresponding dedicated paper reading section in the book — it is recommended to read selectively according to your learning progress.
💡 Deep Reading Section Index :
Paper Authors Year Book Chapter Link
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Wei et al. (Google Brain) 2022 3.3 arXiv:2201.11903 Large Language Models are Zero-Shot Reasoners Kojima et al. 2022 3.3 arXiv:2205.11916 Self-Consistency Improves Chain of Thought Reasoning Wang et al. (Google Brain) 2023 3.3, 17.2 arXiv:2203.11171 Tree of Thoughts: Deliberate Problem Solving with LLMs Yao et al. (Princeton) 2023 3.3 arXiv:2305.10601 ReAct: Synergizing Reasoning and Acting in Language Models Yao et al. (Princeton) 2022 3.3, 6.2 arXiv:2210.03629 Plan-and-Solve Prompting Wang et al. 2023 6.3 arXiv:2305.04091
Paper Authors Year Book Chapter Link
Toolformer: Language Models Can Teach Themselves to Use Tools Schick et al. (Meta) 2023 4.1 arXiv:2302.04761 Gorilla: Large Language Model Connected with Massive APIs Patil et al. (UC Berkeley) 2023 4.1 arXiv:2305.15334 ToolLLM: Facilitating LLMs to Master 16000+ Real-world APIs Qin et al. 2023 4.1 arXiv:2307.16789 ToolACE: Winning the Points of LLM Function Calling Liu et al. (Huawei Noah's Ark & USTC) 2024 4.6 arXiv:2409.00920 RAG-MCP: Mitigating Prompt Bloat in LLM Tool Selection Gan et al. 2025 4.6 arXiv:2505.03275
Paper Authors Year Book Chapter Link
Voyager: An Open-Ended Embodied Agent with LLMs Wang et al. (NVIDIA & Caltech) 2023 5.6 arXiv:2305.16291 CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets Yuan et al. (Peking University) 2024 5.6 arXiv:2309.17428
Paper Authors Year Book Chapter Link
Generative Agents: Interactive Simulacra of Human Behavior Park et al. (Stanford) 2023 5.1 arXiv:2304.03442 MemGPT: Towards LLMs as Operating Systems Packer et al. (UC Berkeley) 2023 5.1 arXiv:2310.08560 MemoryBank: Enhancing LLMs with Long-Term Memory Zhong et al. 2023 5.1 arXiv:2305.10250 Cognitive Architectures for Language Agents (CoALA) Sumers et al. 2023 5.1 arXiv:2309.02427 HippoRAG: Neurobiologically Inspired Long-Term Memory for LLMs Gutiérrez et al. (OSU) 2024 5.6 arXiv:2405.14831 Zep: A Temporal Knowledge Graph Architecture for Agent Memory Rasmussen et al. 2025 5.6 arXiv:2501.13956
Paper Authors Year Book Chapter Link
Reflexion: Language Agents with Verbal Reinforcement Learning Shinn et al. 2023 6.4 arXiv:2303.11366 Self-Refine: Iterative Refinement with Self-Feedback Madaan et al. (CMU) 2023 6.4 arXiv:2303.17651 CRITIC: LLMs Can Self-Correct with Tool-Interactive Critiquing Gou et al. 2023 6.4 arXiv:2305.11738 Large Language Models Cannot Self-Correct Reasoning Yet Huang et al. 2023 6.4 arXiv:2310.01798
Paper Authors Year Book Chapter Link
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks Lewis et al. (Meta AI) 2020 7.1 arXiv:2005.11401 Self-RAG: Learning to Retrieve, Generate, and Critique Asai et al. 2023 7.1 arXiv:2310.11511 Corrective Retrieval Augmented Generation (CRAG) Yan et al. 2024 7.1 arXiv:2401.15884 From Local to Global: A Graph RAG Approach Edge et al. (Microsoft) 2024 7.1 arXiv:2404.16130 LightRAG: Simple and Fast Retrieval-Augmented Generation Guo et al. (HKU) 2024 7.6 arXiv:2410.05779
Paper Authors Year Book Chapter Link
ReAct: Synergizing Reasoning and Acting in Language Models Yao et al. (Princeton) 2022 6.2 arXiv:2210.03629 Plan-and-Solve Prompting Wang et al. 2023 6.3 arXiv:2305.04091 Reflexion: Language Agents with Verbal Reinforcement Learning Shinn et al. 2023 6.4 arXiv:2303.11366 Learning to Reason with LLMs (OpenAI o1) OpenAI 2024 6.6 openai.com DeepSeek-R1: Incentivizing Reasoning Capability via RL DeepSeek-AI 2025 6.6 arXiv:2501.12948
Paper Authors Year Book Chapter Link
MetaGPT: Meta Programming for Multi-Agent Collaboration Hong et al. 2023 14.1 arXiv:2308.00352 Communicative Agents for Software Development (ChatDev) Qian et al. 2023 14.1 arXiv:2307.07924 AutoGen: Enabling Next-Gen LLM Applications Wu et al. (Microsoft) 2023 14.1 arXiv:2308.08155 AgentVerse: Facilitating Multi-Agent Collaboration Chen et al. 2023 14.1 arXiv:2308.10848 Magentic-One: A Generalist Multi-Agent System Fourney et al. (Microsoft) 2024 14.6 arXiv:2411.04468 Multi-Agent Collaboration Mechanisms: A Survey of LLMs Nguyen et al. 2025 14.6 arXiv:2501.06322
Paper Authors Year Book Chapter Link
Not What You've Signed Up For: Indirect Prompt Injection Greshake et al. 2023 17.1 arXiv:2302.12173 HackAPrompt: Exposing Systemic Weaknesses of LLMs Schulhoff et al. 2023 17.1 arXiv:2311.16119 FActScore: Fine-grained Atomic Evaluation of Factual Precision Min et al. (UW) 2023 17.2 arXiv:2305.14251 A Survey on Hallucination in Large Language Models Huang et al. 2023 17.2 arXiv:2311.05232 InjecAgent: Benchmarking Indirect Prompt Injections in Tool-Integrated Agents Zhan et al. 2024 17.6 arXiv:2403.02691 AgentDojo: Dynamic Environment for Agent Attack/Defense Debenedetti et al. (ETH Zurich) 2024 17.6 arXiv:2406.13352 Agent Security Bench (ASB): Attacks and Defenses in LLM Agents Zhang et al. 2025 17.6 arXiv:2410.02644
Paper Authors Year Description Link
A Survey on Large Language Model based Autonomous Agents Wang et al. (Renmin University) 2023 Most comprehensive LLM Agent survey arXiv:2308.11432 The Rise and Potential of Large Language Model Based Agents: A Survey Xi et al. 2023 Survey on the rise and potential of Agents arXiv:2309.07864 LLM Powered Autonomous Agents Lilian Weng (OpenAI) 2023 Excellent technical blog, suitable for beginners lilianweng.github.io Multi-Agent Collaboration Mechanisms: A Survey of LLMs Nguyen et al. 2025 Survey on multi-Agent collaboration mechanisms arXiv:2501.06322
💡 Reading Recommendation : If time is limited, prioritize these 7 "must-read" papers: ① ReAct (basic Agent paradigm) ② Generative Agents (memory system design) ③ Original RAG paper (knowledge augmentation) ④ Reflexion (self-improvement) ⑤ DeepSeek-R1 (reasoning model, 2025) ⑥ Magentic-One (general multi-Agent system, 2024) ⑦ A Survey on LLM based Autonomous Agents (panoramic survey).
The Agent field evolves rapidly. It is recommended to follow:
LangChain Blog — Framework updates and best practicesOpenAI Blog — Model capability updates and Agents SDK developmentAnthropic Blog — Claude model and MCP protocol updatesGoogle AI Blog — Gemini model and A2A protocol developmentsThe Batch (by Andrew Ng) — Weekly AI industry newsletterarXiv — Latest research papers (search "LLM Agent")DeepSeek Blog — Latest developments in open-source reasoning models
