Introduction to Agentic AI
AGAI 101
A broad, conceptual introduction to Agentic AI as a discipline. Explore what AI agents are, how they reason, plan, and act in the world, and why agentic systems represent a paradigm shift in how we build and deploy AI.
What Is Agentic AI?
Agentic AI refers to AI systems that do not merely respond to single inputs but act autonomously over time to accomplish goals. Where a traditional AI model answers a question, an agentic system plans, takes actions, observes results, and adapts — much like a person working through a problem.
This course gives you a panoramic view of the entire field — from the foundational concepts of language models to the emerging world of autonomous agents capable of browsing the web, writing code, managing files, and collaborating with other agents.
Why Agentic AI Matters Now
For most of AI's history, models were tools: you gave them input, they gave you output. That has changed. Modern AI agents can decompose complex tasks, use external tools, maintain memory across sessions, and coordinate with other agents to complete work that previously required human effort.
Understanding how these systems work — and how to build, evaluate, and constrain them — is one of the most important skills in technology today.
What You Will Learn
This course introduces the key ideas you need to understand the rest of the curriculum: what makes a system "agentic," how language models serve as the reasoning core of agents, what tools and memory mean in this context, and what challenges arise when AI systems act with greater autonomy.
Who This Course Is For
This course is for anyone who wants to understand how agentic AI works. You might be a developer curious about AI APIs, a product manager evaluating AI tooling, a student beginning a deeper study of AI, or a professional trying to understand how AI will affect your field. No prior AI experience is required.
What you will learn
- Define an AI agent and distinguish it from a traditional AI model
- Explain the agent loop and how agents perceive, reason, and act
- Describe the roles of tools, memory, and planning in agentic systems
- Identify major categories of AI agents and their use cases
- Articulate the key risks and limitations of autonomous AI systems
Major topics
Why this course matters
Agentic AI is transforming how software is built and how work gets done. Understanding the foundations of agentic systems gives you the mental models to evaluate new tools, build responsibly, and anticipate where the field is heading.
Course modules
What is Agentic AI?
Understand what makes an AI system agentic, how agentic systems differ from ordinary AI tools, and why the shift from passive prediction to goal-directed action matters.
Agents, Tools, and Environments
Learn how agents interact with external systems through tools, operate inside environments, and use memory to maintain context across steps.
Building Your First Agent
Apply practical design principles to build a simple, safe, observable, and useful AI agent.
Common misconceptions
AI agents are fully autonomous and do not need human oversight
Agentic AI is just a chatbot with extra steps
All AI agents use the same architecture
Bigger language models automatically make better agents
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