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Frontend Architecture and Performance for AI Apps

Build a fast, clear and safe screen for AI work. You turn Larkfield's ticket API into a real help-desk interface with React and TypeScript, show AI drafts as they are written, track slow AI jobs, and prove every speed-up with a measurement in the browser.

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What you'll learn

By the end of this course, you will be able to:

  • Understand browser and frontend application fundamentals.
  • Organize components and state around clear responsibilities.
  • Build reliable interfaces for streaming and background AI work.
  • Measure and improve browser performance and accessibility.

About this course

Larkfield’s help-desk agents use the ticket API through curl and the API’s documentation page. Grace, the support lead, asks for a real screen: a ticket list that stays fast with thousands of tickets, a ticket view that shows the AI draft as it is written, and clear messages when slow AI work is still running or has failed.

In this course, you build that screen one module at a time. If you have never written HTML, CSS or JavaScript, the first module teaches them from the start, with the ticket API you already know. Then you build the interface with React and TypeScript: small components with clear jobs, and data from the API that stays correct while people work.

Next you add the parts that AI work needs. A draft appears word by word and stops when you press Stop. A slow job shows whether it is waiting, running or failed. Every draft shows its sources and whether a person must check it.

Finally you make the interface fast, safe and usable for everyone. You measure in the browser before you change anything, render the model’s text without letting it run code, keep secrets out of the browser, and complete every task by keyboard. Everything runs on your computer, including a mock ticket API whose AI answers were recorded from real models in earlier courses.

Before you start

You completed Build and Deploy Your First API, or you have the same skills. If you already build web interfaces with JavaScript, you can pass the entry task of the first module and start with the second. You do not need an account or money. The ticket API in this course is a mock that runs on your computer; its AI answers are recorded or simulated.

Courses to take first: Build and Deploy Your First API.

Who this is for

People who can build and call a small API, as in Build and Deploy Your First API, and who now need a browser interface for an AI feature. You do not need to know HTML, CSS or JavaScript; the first module teaches them. Developers and AI engineers who must put an AI service in front of real users.

How we made this course

Experienced AI practitioners designed this course. AI helped us draft the content; people chose the teaching approach and the examples, and reviewed every lesson. The outputs that you see are the actual results of running the code. How we make our courses

Inside the course

Module 2Components and application structure

3 lessons

Build the interface from components. Learn React's components, props and state, split a large screen by responsibility, and understand when React draws again and why.

  1. React basics75 min
  2. Organize by responsibility50 min
  3. Rendering and effects80 min

Module 3Data fetching and state management

3 lessons

Fetch data that stays correct. Separate what the user chose from what the server stores, cache and refresh answers, page through thousands of tickets, and never let an old search overwrite a new one.

  1. Local versus server state50 min
  2. Query lifecycle60 min
  3. Pagination and forms75 min

Module 5Performance and scalability

3 lessons

Make it fast with evidence. Measure bundle size, rendering time and waiting time in the browser, load less work with code splitting and virtualization, and choose how the pages are rendered.

  1. Measure the browser55 min
  2. Load less work55 min
  3. Architecture decisions65 min

Module 6Security, accessibility and handoff

3 lessons

Make it safe, accessible and ready to hand over. Render generated text safely, keep secrets out of the browser, make every task work by keyboard and screen reader, and test it from components to one full flow.

  1. Browser security boundaries55 min
  2. Accessible interaction55 min
  3. Test and deliver55 min

After the case studiesFinal assignment

Use every module in one practice project. You collect evidence, and check it against the course outcomes.

  1. Final assignment180 min

Case studies

Realistic projects from start to finish, on real data, with every output explained. Each one makes a portfolio piece. Complete at least one for the certificate; the others are optional.

  1. Fast search over a public dataset2 hr 30 min

    Build a search interface over an open dataset with server paging, stale-response handling and virtualization, and measure it.

  2. Make an AI chat interface accessible2 hr

    Make a chat interface usable by keyboard and screen reader: focus, labels and announcements that do not read every token, tested with the browser's accessibility tree.

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