What is Agentic AI?
Discover what makes AI agents different from traditional LLMs and why they represent the next evolution in AI
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0 / 5 completedInteractive Demo
Experience agentic AI in action! Watch how an agent reasons, acts, and achieves goals through interactive demonstrations.
In this interactive simulator, you'll see the ReAct (Reasoning + Acting) pattern in real-time. Select a task below and watch the agent work through it step-by-step, showing you exactly how it thinks, which tools it calls, and how it interprets results.
๐คInteractive Agent Simulator
What You Just Witnessed
The agent simulator above demonstrates the core loop of agentic AI:
Reasoning
The agent analyzes the situation, determines what information it needs, and plans its next action.
Acting
It executes actions using tools: calling APIs, searching databases, running code, or manipulating files.
Observing
It processes the results, learns from the output, and decides whether to continue or conclude the task.
๐ฏKey Insights
- โIterative Process: Agents don't just execute onceโthey loop through reasoning, acting, and observing until the goal is achieved.
- โTool Selection: The agent chooses the right tool for each subtask. Weather API for weather, web search for research, code interpreter for programming.
- โContext Awareness: Each step builds on previous observations. The agent maintains state and adjusts its strategy based on results.
- โError Handling: If a tool fails or returns unexpected data, the agent can retry with different parameters or choose an alternative approach.
๐ก Real-World Scale: In production, agents might execute 50-100 steps, call dozens of APIs, and work for minutes or hours to complete complex tasks like "analyze competitor pricing and generate a strategic report." The demos above are simplified to show the core mechanics.