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What AI Agents Are and How to Build One - AI Foundations Day 12

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What AI Agents Actually Are

4:02 with Travis Alstrand

The difference between AI that answers and AI that acts, what agents can already do right now, the four components every agent is built from, and where they live across Claude, ChatGPT, Gemini, and Perplexity. If the structure sounds like a well-written prompt, that's the point.

This is part of the AI Bootcamp. Click here to learn more.

Vocabulary

  • Agent — AI that takes action rather than just producing text. You give it a goal; it picks the steps, uses tools, and works until the job is done. A chatbot answers questions; an agent completes tasks.
  • API (Application Programming Interface) — How two pieces of software talk to each other. Like a waiter: your app sends a request, the API carries it to the other system and brings back the result.
  • Database — Where your app stores information that has to stick around — accounts, saved items, history. Data not saving, duplicating, or vanishing is a database issue.
  • Model Context Protocol (MCP) — An open standard that connects an AI model to outside tools and data so it can actually use them, not just talk about them.

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    Welcome to day 12 of the program. Yesterday we previewed the web app track, 0:00
    building software with screens and interfaces that people click through. 0:02
    Today is the second Build Track preview, Agents. 0:06
    Up to this point, everything you've done with AI has been conversational. 0:10
    You ask a question, AI answers. You give it a task, it responds. 0:14
    You're always in control, guiding every step. 0:19
    Agents work differently. An agent is AI that can take action, not 0:21
    just generate responses. 0:26
    You give it a goal and it figures out the steps, uses tools, makes decisions, 0:28

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