Cursor 2.0: Crash Course for Beginners

Reviews Cursor 2.0, focusing on its new Composer AI model and the ability to run multiple AI agents simultaneously on the same prompt. I demonstrate these features using a React Native app I built, showing how Cursor 2.0 can help revamp a paywall UI quickly.

If you want to level up your React Native skills, check out my course at codeto.dev. This tutorial is for developers curious about AI coding assistants and how to integrate them into mobile app workflows.

What's inside

• Introduction to Cursor 2.0 and the Composer AI model
• Running multiple AI agents simultaneously with the new agents tab
• Using Cursor 2.0 in a React Native app for a real-world UI revamp
• Adding images and context to AI prompts with the built-in browser
• Crafting effective prompts for UI improvements
• Comparing Composer, Sonnet 4.5, and GPT5 CodeX models
• Reviewing and applying AI-generated code changes
• Handling issues and undoing changes after AI code generation

Introduction to Cursor 2.0 and the Composer AI model

Cursor 2.0 introduces a new AI model called Composer, designed to be fast and smart for coding tasks. The team announced it just days before this video. Composer is an in-house model optimized for speed, capable of delivering results in under 30 seconds, which is impressive for AI-assisted coding.

This update also adds a new agents tab that lets you run the same prompt across multiple AI models at once. Composer is the highlight, but you can also select other popular models like Sonnet 4.5 and GPT5 CodeX for comparison.

Running multiple AI agents simultaneously with the new agents tab

One of the coolest features in Cursor 2.0 is the ability to run up to four AI agents simultaneously on the same prompt. This means you can test different models side-by-side and compare their outputs before deciding which code to keep.

You select your models in the agents tab, then submit your prompt once. The UI shows the progress of each agent, and you can review all generated changes in one place. This is a huge time saver and a unique feature I hadn’t seen before in AI coding tools.

Using Cursor 2.0 in a React Native app for a real-world UI revamp

I used Cursor 2.0 to improve the paywall UI of my React Native app called AI Tattoo. The app was rejected by Apple due to missing terms and privacy policy, but the UI revamp was a perfect use case to test Cursor’s new features.

I showed how to load the existing UI file, add context, and ask the AI to revamp the visual layout and hierarchy without changing core functionality. This practical demo highlights how AI can speed up UI improvements in mobile apps.

Adding images and context to AI prompts with the built-in browser

Cursor 2.0 now supports adding images and extra context to your AI prompts. I used OpenAI’s new browser, CHP Atlas, to find screenshots of paywall UIs and pasted them into the prompt. I also included an image asset from my app to guide the AI’s design choices.

This feature helps the AI understand your design goals better and produce more relevant UI code. You just mention the image in the prompt, and Cursor automatically includes it for all selected agents.

Crafting effective prompts for UI improvements

I’m not great at writing prompts, so I asked ChatGPT to help generate a clear and detailed prompt for revamping the paywall UI. The prompt specified that the AI should improve the visual appeal and layout without changing business logic or functionality.

I included details about the three subscription plans and asked the AI to take inspiration from the screenshots and tattoo image asset. This shows how combining AI tools can help you craft better prompts for coding assistants.

Comparing Composer, Sonnet 4.5, and GPT5 CodeX models

I ran the UI revamp prompt on three models: Composer, Sonnet 4.5, and GPT5 CodeX. Composer was the fastest and generated less code with fewer deletions, focusing on concise improvements. Sonnet produced more extensive changes and detailed explanations, which might explain its slower speed.

GPT5 CodeX was the slowest but sometimes generated interesting results. This comparison helps you understand the tradeoffs between speed, verbosity, and quality when choosing an AI model for your coding tasks.

Reviewing and applying AI-generated code changes

After the agents finished, I reviewed the suggested code changes in Cursor’s interface. You can see diffs, added components like linear gradients and blur views, and decide which changes to apply.

Applying all changes is safe because you can always undo them. This workflow lets you experiment with AI-generated code confidently and pick the best improvements for your project.

Handling issues and undoing changes after AI code generation

One challenge I faced was that Sonnet created a README file that didn’t exist in my project, preventing me from applying its changes directly. I asked the AI to remove that file from the changes and retried.

Also, after applying some changes, the app broke, so I used Cursor’s undo feature to revert to the previous state. This shows that AI-generated code still requires careful review and testing before merging.

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