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'Agent' is the buzzword of 2025-26. Stripped of hype, it means: AI that can take actions, not just generate text.
An 'AI agent' is just an LLM connected to tools — search engines, APIs, code interpreters, file systems — that the model can choose to use to accomplish a goal. The model loops: think → decide on a tool → call it → read the result → think again. Real autonomy is still limited, but the basic loop runs every minute on millions of computers now.
On chatgpt.com, ask 'Use the web to research X, then write me a 3-paragraph summary with sources.' That's a 1-step agentic loop already running for you. Now imagine 50 steps. That's where the field is going.
8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-builders-foundations-ai-agentic-workflows-explained-r9a10-teen
What is the main idea of "What People Mean When They Say 'AI Agent'"?
Which concept is most central to "What People Mean When They Say 'AI Agent'"?
Which use of AI fits this topic best?
What should a careful learner remember about "The rule"?
You want to use AI after this lesson. What is the safest next step?
How should AI output about agent be treated?
Name one way to verify an AI answer about agent.
Which action would help you apply "What People Mean When They Say 'AI Agent'" responsibly?