Continuously Updated · 2026 Summer Edition

Resource Hub

Papers, courses, books, communities, podcasts, newsletters — we curate every worthwhile piece of content, organized by learning stage, sorted by time, archived by topic.

Must-Read Papers

25 papers that shaped the Agent field

In learning order. Each has a summary, reading value, and recommendation.

Foundational
ReAct Series
Memory & Retrieval
Multi-Agent
Evaluation
2022 · ReAct

ReAct: Synergizing Reasoning and Acting in Language Models

Princeton / Google · Yao et al.

For the first time systematically proposed the "think-act-observe" loop. The foundational work of Agent paradigms.

2020 · CoT

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Google · Wei et al.

Revealed that "think step by step" significantly improves LLM performance on complex reasoning.

2017 · Transformer

Attention Is All You Need

Google · Vaswani et al.

The original Transformer paper. The foundation of all modern LLMs and Agents.

2020 · RAG

Retrieval-Augmented Generation for Large Language Models

Meta AI · Lewis et al.

Foundational RAG work: enables LLMs to access external knowledge bases.

2023 · Function Calling

GPT-4 Technical Report

OpenAI

Function Calling capability description, foundation of modern Agent tool calling.

2023 · Tree of Thoughts

Tree of Thoughts: Deliberate Problem Solving with LLMs

Princeton · Yao et al.

Extends CoT to tree structure with backtracking and branching exploration.

2023 · Reflexion

Reflexion: Language Agents with Verbal Reinforcement Learning

Northeastern · Shinn et al.

Lets Agents self-improve by "reflecting on failure". Source of Self-Refine, Reflexion modes.

2024 · o1

OpenAI o1 / Learning to Reason with LLMs

OpenAI

Inference-time compute revolution: more thinking tokens = better performance.

2023 · MemGPT

MemGPT: Towards LLMs as Operating Systems

UC Berkeley · Packer et al.

Revolutionary hierarchical memory: Agent as OS with layered memory tiers.

2024 · GraphRAG

From Local to Global: A Graph RAG Approach

Microsoft Research

Combines knowledge graphs with RAG for global questions.

2023 · AutoGen

AutoGen: Enabling Next-Gen LLM Apps via Multi-Agent Conversation

Microsoft · Wu et al.

2023 · MetaGPT

MetaGPT: Meta Programming for Multi-Agent Collaboration

Hong et al.

2023 · AgentBench

AgentBench: Evaluating LLMs as Agents

Tsinghua · Liu et al.

Most authoritative Agent evaluation benchmark: multi-scenario, multi-task.

2024 · SWE-bench

SWE-bench: Can LMs Resolve Real-World GitHub Issues?

De facto standard for evaluating coding Agents, based on real GitHub issues.

Courses & Books

Systematic learning resources

Recommended Books

Books worth repeated reading

📕

Designing Data-Intensive Applications

Martin Kleppmann. Classic bible of data system design.

📚 Engineering · O'Reilly
📗

AI Agents in Action

Michael Lanham · Manning 2025. A practical book specifically on AI Agent design.

📚 Agent Practice · Manning
📘

Prompt Engineering for LLMs

John Berryman et al. Deep-dive on prompt engineering essentials.

📚 Prompt · O'Reilly
📙

Building LLM Applications

O'Reilly short books covering RAG, Agent, Embeddings.

📚 LLM Engineering
Community

Find your learning peers

💬 LangChain Discord

Most active English-speaking Agent developer community.

Join →

🐦 Twitter/X AI Circle

Follow @hwchase17, @yann_lecun, @karpathy and other top practitioners.

🇨🇳 Chinese Communities

AI Agent topics on Jike, Zhihu, Juejin. WeChat Reading academic accounts.

📺 YouTube Channels

Sam Witteveen, James Briggs, Dave Ebbelaar for high-quality Agent tutorials.

📮 r/LocalLLaMA

Reddit's local LLM and Agent sub-community.

🏗 OpenAI Developer Forum

OpenAI's official forum for Function Calling, Assistants API questions.

Newsletter

Stay on the cutting edge

📰 Import AI

Jack Clark · Weekly curated AI events and papers.

📰 TLDR AI

5 minutes of this week's AI news. Minimalist style.

📰 LangChain Newsletter

Official updates, new features, user stories.

📰 AlphaSignal

Deep dives on latest AI papers and OSS projects.

📰 The Rundown AI

Comprehensive daily, from news to tools.

📰 Ahead of AI

Sebastian Raschka · Academic deep dives.