LLM Agent Cookbook: From ReAct to Multi-Agent in 4 Weeks

LLM Agent Cookbook: From ReAct to Multi-Agent in 4 Weeks

Not sure where to start with LLM Agent development? You've heard of the ReAct pattern but don't know how to implement it? Curious about LangGraph and building multi-agent systems with CrewAI? This Cookbook has the answers.

Why LLM Agents?

LLMs like ChatGPT and Claude are powerful but have limitations:

• No access to real-time information
• Cannot interact with external systems
• Cannot execute complex multi-step tasks

Agents overcome these limitations. Give an LLM tools, and let it reason and act autonomously.

Curriculum Overview

Week 1: Foundations

• Understanding and implementing the ReAct pattern
• How Tool Calling works
• Designing robust schemas with Pydantic

Week 2: Enhanced Reasoning

• RAG and Memory systems
• Building complex workflows with LangGraph
• Improving retrieval quality with Self-RAG

Week 3: Multi-Agent Systems

• Building teams with CrewAI
• MCP and Agent-to-Agent communication
• Orchestration with Supervisor patterns

Week 4: Production Deployment

• Building safety with Guardrails
• Implementing Human-in-the-Loop
• Deploying with FastAPI + Docker
• Prompt optimization with DSPy

Key Features

• Hands-on Jupyter Notebook exercises
• Weekly real-world projects
• Solution code available on GitHub
• Bilingual support (Korean/English)
• Integration with DrillCheck AI interview practice

Who Is This For?

• Those with basic Python knowledge
• Anyone with LLM API experience
• Developers wanting to build their own agents
• Engineers looking to deploy agents in production

Get Started

Start building production-ready LLM Agents in just 4 weeks with this free Cookbook.

Go to LLM Agent Cookbook