Agentic AI & LLM Agents

Master AI Agents and Agentic AI systems. 8 comprehensive chapters covering agent architectures, tool-using agents, ReAct framework, multi-agent systems, agent orchestration, and building production agents with detailed explanations, formulas, and code examples.

Chapter 1: Introduction to AI Agents

What are Agents? Why Agents?

  • What is an AI agent? Definition and characteristics
  • Agents vs traditional LLMs
  • Agent capabilities (reasoning, tool use, memory)
  • Types of agents (simple, tool-using, multi-agent)
  • Agent architecture overview
Foundation Agents Architecture

Chapter 2: Agent Architecture Components

Building Blocks of Agents

  • LLM as the reasoning engine
  • Memory systems (short-term, long-term)
  • Tool/function calling interface
  • Planning and decision-making
  • Action execution and observation
Architecture Memory Tools

Chapter 3: Tool-Using Agents

Agents That Can Use Tools

  • Function calling and tool definition
  • Tool selection and execution
  • Tool results integration
  • Error handling in tool usage
  • Building tool-using agents
Tools Function Calling Integration

Chapter 4: ReAct Framework

Reasoning + Acting

  • ReAct: Reasoning and Acting in language
  • Thought-Action-Observation loop
  • Step-by-step reasoning process
  • ReAct implementation
  • ReAct vs other agent frameworks
ReAct Reasoning Loop

Chapter 5: Agent Frameworks & Libraries

Building Agents with Frameworks

  • LangChain agents
  • AutoGPT and BabyAGI concepts
  • LlamaIndex agents
  • Custom agent frameworks
  • Framework comparison
Frameworks LangChain AutoGPT

Chapter 6: Multi-Agent Systems

Agents Working Together

  • Why multi-agent systems?
  • Agent communication and coordination
  • Specialized agents (researcher, writer, reviewer)
  • Agent hierarchies and workflows
  • Multi-agent implementation
Multi-Agent Coordination Workflows

Chapter 7: Agent Orchestration & Workflows

Managing Complex Agent Systems

  • Orchestration patterns
  • Sequential vs parallel agent execution
  • Conditional routing and decision trees
  • State management across agents
  • Workflow implementation examples
Orchestration Workflows State

Chapter 8: Building Production Agents

Production-Ready Agent Systems

  • Agent evaluation and testing
  • Error handling and recovery
  • Monitoring and observability
  • Cost optimization
  • Deployment and scaling
Production Deployment Monitoring