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Module 01 · Page 2 of 20 · 6 sections

Introduction to Agentic AI

What agentic AI is, how it differs from traditional AI, and where it is already used.

02Agent Architecture and Components03Types of Agents18Challenges, Limitations and Future of Agentic AI
1.1

What is Agentic AI?

  • Agentic AI refers to AI systems that can plan, reason, take actions and achieve goals autonomously with minimal human intervention.
  • Unlike traditional AI, which only responds to queries, agentic AI can understand the goal, make decisions, use tools and complete complex multi-step tasks.
  • It combines the capabilities of LLMs with planning, memory, tool use and reasoning to work like an intelligent agent.
1.2

Key Characteristics

1
Autonomy
Can operate with minimal human input.
2
Goal-Oriented
Works towards achieving specific goals.
3
Planning & Reasoning
Breaks complex tasks into smaller steps.
4
Tool Use
Can use external tools, APIs and systems.
5
Memory
Maintains short-term and long-term memory.
6
Adaptability
Learns from feedback and environment.
7
Multi-step Execution
Can handle complex workflows.
8
Self-Improvement
Can improve based on experience.
1.3

Agentic AI vs Traditional AI

AspectTraditional AIAgentic AI
NatureReactiveProactive and autonomous
Goal handlingSingle stepMulti-step and complex
Decision makingPredefined rules / model responsePlans and reasons dynamically
Tool usageUsually notCan use external tools
MemoryLimited / noneShort-term and long-term
AdaptabilityFixed behaviourLearns and adapts
ExampleChatGPT (Q&A)AI agent for research, analysis, automation
1.4

How Agentic AI Works

User Goal / Task
PlanningTask decomposition
Agent
MemoryShort-term & long-term
Tool UseAPIs, search, code, etc.
Action ExecutionMulti-step tasks
Result / Output
The agent loop: plan, act through tools, observe the result and feed it back.
Related02Agent Architecture and Components05Planning and Reasoning in Agentic AI
1.5

Examples of Agentic AI

1
Research Agent
Automatically search, read, summarize and create reports on a topic.
2
Code Agent
Write, debug and execute code using tools like IDE, terminal and documentation.
3
Data Analyst Agent
Analyze data, generate insights and create visualizations.
4
Personal Assistant Agent
Manage emails, calendar, travel plans and daily tasks.
5
Web Automation Agent
Interact with websites to complete tasks (form filling, booking, etc.).
6
Multi-Agent System
Multiple agents collaborating to solve complex problems.
7
Enterprise Agent
Automate business workflows using internal tools and APIs.
Related08Multi-Agent Systems in Agentic AI09Building Real-World Projects with Agentic AI
1.6

Real-World Applications

1
Customer Support
Intelligent agents to handle user queries and automate resolutions.
2
Software Development
Code generation, testing and deployment automation.
3
Healthcare
Patient data analysis and research assistance.
4
Finance
Market analysis, risk assessment and report generation.
5
Education
Personalized learning and tutoring agents.
6
Operations
Process automation and workflow orchestration.
7
Research
Literature review and scientific analysis.