AI Agents: Architecture, Implementation, and Practical Applications

A comprehensive technical guide for software developers covering AI agent concepts, architectures, frameworks, and real-world implementation strategies.

29
Comprehensive Slides
7
Technical Sections
5000+
Lines of Code Examples

Complete Learning Path

Navigate through our comprehensive curriculum designed for software developers. Each section builds upon the previous, taking you from basic concepts to production deployment.

1

Introduction & Foundations

Core concepts, definitions, and fundamental understanding

1
AI Agents

Title & Introduction

Professional introduction to the comprehensive AI agents presentation

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2
Learning Objectives

Agenda & Objectives

Learning outcomes and comprehensive roadmap for developers

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3
What Are Agents?

What Are AI Agents?

Technical definitions with extensive code examples and comparisons

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4
Evolution

Evolution from Traditional AI

Technical progression and architectural comparisons

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5
Why Agents Matter

Why AI Agents Matter

Impact analysis for developer workflows and productivity

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6
Comparisons

Agent vs Assistant vs Chatbot

Detailed technical distinctions with implementation examples

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2

Agent Types & Classification

Understanding different agent architectures and their capabilities

7
Five Types

Five Agent Types Overview

Complete classification framework and complexity spectrum

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8
Reflex Agents

Reflex Agents

Simple and model-based architectures with implementation patterns

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9
Goal & Utility

Goal & Utility-Based Agents

Planning algorithms and optimization strategies

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10
Learning Agents

Learning Agents

Most advanced adaptive systems with ML integration

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11
Multi-Agent

Multi-Agent Systems

Collaboration patterns and coordination mechanisms

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