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LLM Agents: From Zero to One

LLM agents are gaining quite some momentum in the generative AI space since they can process feedback, maintain memory, strategize for future actions, and collaborate with various tools to make informed decisions.

If you’ve been looking to learn more about LLM agents and maybe even create your own, this roadmap is just for you! It's filled with great free resources to help you get started and stay up-to-date on what's happening in the world of agents.

agent_roadmap_image.gif

Roadmap

Day 1: Introduction to Agents

  1. LLM Agents glossary by Deepchecks (link)
  2. Navigating the World of LLM Agents: A Beginner’s Guide by Dominik Polzer (link)

Day 2: Core Components

  1. Harrison Chase - Agents Masterclass from LangChain Founder (link)
  2. Introduction to LLM Agents by Nvidia (link)

Day 3: Multi-Agents & Evaluation

  1. Revolutionizing AI: The Era of Multi-Agent Large Language Models by Gary Fowler (link)
  2. Multi-Agent LLM Applications | A Review of Current Research, Tools, and Challenges by Victor Dibia (link)
  3. How to Build, Evaluate, and Iterate on LLM Agents by Deeplearning.AI (link)
  4. Benchmarks for evaluating agents (read any one):
    1. AgentBench
    2. IGLU
    3. ClemBench
    4. ToolBench
    5. GentBench

Day 4- Real-World Agents

  1. Harrison Chase - Agents Masterclass from LangChain Founder (link)

  2. What's next for AI agents ft. LangChain's Harrison Chase (link)

  3. Scaling AI Agents for Real-World Tasks with Parcha CEO AJ Asver (link)

  4. Learn about popular real world agents (read any one):

    • ChemCrow: Augmenting large-language models with chemistry tools (link)
    • BabyAGI (link)
    • OS-Copilot: Towards Generalist Computer Agents with Self-Improvement (link)

  5. Use these Github repos to check out the latest research in agents (use this as a reference only; it’s not required to read through everything)

Day 5- Build Your Own Agent

Choose any one of these resources and follow the implementation guide in them to get started

  1. Episode #1: Intro to LLM Agents: When RAG is Not Enough by Neurons Lab (link)
  2. Build Anything with AI Agents, Here's How by David Ondrej (link)
  3. The Complete Guide to Building AI Agents for Beginners by VRSEN(link)
  4. Building a LangChain Custom Medical Agent with Memory by ****Sam Witteveen (link)
  5. Langchain Agents [2024 UPDATE] - Beginner Friendly by Ryan Nolan Data (link)
  6. AI Agents in LangGraph course by Deeplearning.AI (Link)
  7. Multi-agent Conversation Framework on Microsoft Autogen (Link)

Other comprehensive resources:

  1. My “Agents 101” guide (link)
  2. LLM Powered Autonomous Agents by Lilian Weng (link)
  3. LLM Agents by Prompt Engineering Guide (link)
  4. LangChain and the Future of LLM Agents by Arize AI (link)