Agentic AI Foundations
Core Concepts: 8 chapters covering the agent loop, ReAct framework, tool-using agents, multi-agent systems, orchestration, and building your first production agent. The recommended starting point before the advanced course.
Course Overview
What You Will Build Toward
- Navigate the Agentic AI Foundations learning path across 8 chapters.
- Choose the right chapter based on your current goal and prerequisites.
- Move from overview material into the canonical chapter experience.
Chapter Path
Start With Any Chapter
Before You Start
Recommended Background
- Working knowledge of the course category.
- Willingness to work through examples and short checks.
Agentic AI Foundations
Core Concepts — 8 chapters covering the agent loop, ReAct framework, tool-using agents, multi-agent systems, orchestration, and building your first production agent. The recommended starting point before the Building Agentic AI Systems advanced course.
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
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
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
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
Chapter 5: Agent Frameworks & Libraries
Building Agents with Frameworks
- LangChain agents
- AutoGPT and BabyAGI concepts
- LlamaIndex agents
- Custom agent frameworks
- Framework comparison
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
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
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