Introduction to Agentic AI
What makes AI "agentic"? Understand the paradigm shift from chatbots to autonomous agents.
What is Agentic AI?
Agentic AI refers to AI systems that can autonomously pursue goals, make decisions, and take actions in the world. Unlike traditional chatbots that simply respond to queries, agentic systems can:
- Plan - Break down complex tasks into smaller steps
- Act - Execute actions using tools and APIs
- Observe - Process the results of their actions
- Adapt - Modify their approach based on feedback
Real Example: Claude Code
When you ask Claude Code to "create a website about AI," it doesn't just tell you how - it actually reads your existing files, writes new code, creates directories, and can even run build commands. It's taking autonomous action to achieve your goal.
The Evolution: From Chatbots to Agents
AI has evolved through several paradigms:
Rule-Based Systems (1960s-1990s)
If-then rules, expert systems. Brittle and limited.
Machine Learning (2000s-2010s)
Pattern recognition, classification. Still passive.
Large Language Models (2020-2022)
GPT, Claude - powerful conversation, but still reactive.
Agentic AI (2023-Present)
LLMs + tools + autonomy. Active problem solvers.
Key Concepts
Why Does This Matter?
Agentic AI represents a fundamental shift in how we interact with computers:
- From commands to goals - Instead of telling the computer exactly what to do, you describe what you want to achieve
- From tools to partners - AI becomes a collaborator that can handle complex, multi-step tasks
- From reactive to proactive - Systems can anticipate needs and take initiative
Think About It
This website you're reading was created by an agentic AI. A human simply asked for "a course site about Agentic AI," and the agent handled everything: creating files, writing code, organizing content, and structuring the navigation. That's the power of agentic systems.
Key Takeaways
- Agentic AI systems can autonomously pursue goals and take actions
- They use tools to interact with the external world
- They reason through problems and adapt their approach
- They represent a paradigm shift from reactive chatbots to proactive assistants