Modern Automated AI Agents: Building Agentic AI to Perform Complex Tasks

Table of contents
Introduction
Modern Automated AI Agents: Introduction
Lesson 1: Introduction to AI Agents
Topics
1.1 Overview of AI Agents and Their Applications
1.2 Leading AI Agent Frameworks
1.3 First Steps with Agents with CrewAI
1.4 Designing Multi-Step Workflows with LangGraph
Lesson 2: Under the Hood of AI Agents
Topics
2.1 Understanding Large Language Models (LLMs)
2.2 Introduction to Tool Integration
2.3 Key Agent Components: Thought, Action, Observation, Response
Lesson 3: Building an AI Agent
Topics
3.1 Building Custom Tools
3.2 Building Our Agent Prompt
3.3 Using Our Agent
Lesson 4: Testing and Evaluating Agents
Topics
4.1 How to Evaluate Agents
4.2 Evaluating Tool Selection and Use
4.3 Assessing the Quality of Agent Responses
4.4 Evaluating Agent Backstories, Task Definitions, and Rules
Lesson 5: Expanding on ReAct with Planning and Reflection
Topics
5.1 Why Agents Fail
5.2 Plan and Execute Agents
5.3 Reflection Agents
Lesson 6: Advanced Applications and Future Directions
Topics
6.1 Exploring Additional Tools and APIs
6.2 Future Trends in AI Agents
Summary
Modern Automated AI Agents: Summary