Welcome to Agentic AI Training

Artificial intelligence is evolving beyond simple question-and-answer interactions. Agentic AI represents systems that can plan, reason, use tools, and take autonomous action to accomplish complex goals.

This training is designed for multiple audiences — whether you're a developer building AI-powered applications, a business analyst evaluating AI use cases, a manager planning team strategy, or a QA engineer testing AI systems.

How This Training Works

• Role-based content: Select your role to see content tailored to your perspective
• Progressive difficulty: Start with fundamentals, unlock advanced content as you progress
• Interactive demos: Try code playgrounds to see concepts in action
• Current data: All model references and benchmarks are kept up-to-date with state-of-the-art (SOTA) tracking

Choose your role and difficulty level in the sidebar to customize your experience.

What Makes AI "Agentic"?

Traditional AI assistants wait for your input and respond. Agentic AI systems go further — they can:

1. Plan multi-step approaches to solve complex problems
2. Use tools to interact with external systems (APIs, databases, files)
3. Observe the results of their actions and adapt their approach
4. Persist through failures by trying alternative strategies
5. Coordinate with other agents or humans to accomplish goals

The Observe → Think → Act Loop

At the core of every agentic system is a loop:

• Observe: Gather information from the environment (read files, check APIs, review results)
• Think: Reason about what to do next based on the goal and current state
• Act: Execute an action using available tools, then observe the result

This loop continues until the goal is achieved or the agent determines it cannot proceed.

From Chatbot to Agent

The most capable models today — including Claude, GPT-4, and Gemini — support the tool use and reasoning capabilities that make agentic behavior possible.

Key Takeaways

Before you move on, here's what to remember from this section:

• Agentic AI goes beyond chatbots — it can observe, think, and act autonomously in a loop
• Tool use is the breakthrough that lets AI systems interact with the real world (APIs, databases, files)
• The AI capability spectrum ranges from simple autocomplete to fully autonomous agents
• Every role benefits differently — developers build agents, analysts use them for data, managers govern them
• Now is the time — foundation models have reached the capability threshold that makes agents practical