Building a Mobile App Using AI - Free AI Course, Chapter 13

Choosing your approach ▶ Watch

Approach	Tools (examples)	Good for
No-code app builders	FlutterFlow, Adalo, Thunkable, Glide	Simple apps, fast prototypes
Cross-platform code + AI assistant	Flutter (Dart), React Native with Expo (JavaScript)	One codebase for Android and iOS
Native code + AI assistant	Kotlin in Android Studio, Swift in Xcode	Best performance and device features
Prompt-to-app builders	AI builders that generate mobile projects	Quick first versions to test ideas

For most beginners, Flutter or React Native (Expo) with an AI coding assistant is the sweet spot: one codebase runs on both Android and iPhone, and the AI can write most of the boilerplate for you. Android Studio and Xcode also include built-in AI coding help.

How a mobile app uses AI ▶ Watch

A mobile app can run a small AI model on the phone, and call a larger cloud model through its backend.

Cloud AI - for chat, writing, complex image understanding. The app calls your backend (for example a cloud function), which holds the API key and calls the model.
On-device AI - for fast, private, offline features such as text recognition, translation, object detection or a small language model. Toolkits include Google ML Kit, LiteRT (formerly TensorFlow Lite), Apple Core ML, and built-in phone AI features such as Gemini Nano on supported Android devices.

Step-by-step: build a "Homework Helper" app ▶ Watch

Define the idea. A student photographs a question and gets a step-by-step explanation.
Sketch the screens. Ask AI: "Suggest a simple 4-screen layout for this app." Draw it on paper or in a design tool.
Set up the project. Install Flutter or Expo; ask the AI assistant to explain each setup step.
Generate the screens. Prompt: "Create a Flutter screen with a camera button, image preview and an Explain button."
Build the backend. A cloud function receives the photo, sends it to a multimodal AI model, and returns the explanation.
Test. Run on an emulator and a real phone. Try bad photos, no internet and long answers.
Polish. Add loading indicators, error messages, dark mode and accessibility labels.
Publish. Create developer accounts, prepare screenshots, a privacy policy and a store listing, then submit for review.

Example: calling your backend from React Native ▶ Watch

async function explain(question) {
  const res = await fetch("https://your-backend.example.com/ask", {
    method: "POST",
    headers: { "Content-Type": "application/json" },
    body: JSON.stringify({ question }),
  });
  const data = await res.json();
  return data.answer;   // no API key in the app!
}

Publishing to the app stores ▶ Watch

Store	Account (at time of writing)	Key requirements
Google Play	One-time registration fee	Privacy policy, data-safety form, content rating, testing
Apple App Store	Annual developer membership	Privacy labels, review guidelines, testing on real devices

Prompts that help when building apps ▶ Watch

"Explain this error message and suggest a fix: [paste error]."
"Refactor this screen into smaller widgets and explain why."
"Write unit tests for this function."
"Review my app for security problems, especially API keys and user data."
"Write a clear, honest privacy policy draft for an app that does [X]" - then have it checked properly.

Chapter summary

Choose no-code, cross-platform (Flutter, React Native) or native development based on your goals.
AI assistants can design screens, write code, explain errors and write tests.
Apps use cloud AI via a secure backend, and on-device AI for fast, private features.
Publishing requires developer accounts, privacy policies and compliance with store rules.