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Web App vs AI Agent vs Data Dashboard - AI Foundations Day 14

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The Three Tracks

4:26 with Travis Alstrand

AI agents, web apps, and data dashboards laid side by side: what each is best suited for, the tools that belong to each, and what your spec needs to define. Plus how to actually choose, starting with which of the last three days you couldn't stop thinking about.

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.
  • Back end — Everything happening behind the scenes — the logic, rules, and processing. The kitchen. Wrong results or mis-handled data are back-end issues.
  • Front end — Everything a user sees and touches — buttons, screens, layouts, forms. The storefront. Broken layouts and dead buttons are front-end issues.
  • Guardrails — Hard boundaries an agent must never cross — the things it's forbidden to do, no matter what it decides.
  • 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 14. Over the last two weeks, you've now 0:00
    experienced all three build 0:01
    paths firsthand. On Day 7, you built a web app using tools 0:02
    like Lovable, Bolt, Replit 0:06
    or v0. Then on Day 11, you saw what it looks like 0:08
    to move beyond simple builders 0:12
    and work directly with the code. On Day 12, you built an AI agent, 0:13
    something that 0:18
    can take actions, use tools and complete tasks autonomously. 0:19
    And on day 13, you worked with real data 0:24
    and built a dashboard from an actual data set. 0:26

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