Replay vs Cursor: Which AI Code Generator Provides the Cleanest Code in 2026?

TL;DR: Replay, leveraging behavior-driven reconstruction from video, consistently generates cleaner, more functional UI code compared to Cursor's screenshot-based approach, especially for complex, multi-page applications.

Replay vs Cursor: Which AI Code Generator Provides the Cleanest Code in 2026?#

The race to automate UI development is heating up. While screenshot-to-code tools have gained traction, they often fall short in capturing the intent behind user interactions. This leads to messy code that requires significant manual cleanup. Enter Replay, a video-to-code engine that uses Gemini to understand user behavior and reconstruct working UI from screen recordings. How does it stack up against established players like Cursor? Let's dive into a head-to-head comparison.

The Problem: Screenshot-to-Code Limitations#

Traditional AI code generators, like those often integrated into IDEs like Cursor, primarily rely on static screenshots. This approach has several inherent limitations:

• •Lack of Context: Screenshots only capture a single visual state. They don't convey the sequence of actions a user takes to reach that state. This makes it difficult for the AI to understand the underlying logic and data flow.
• •Limited Interactivity: Screenshots are static images. They don't represent interactive elements like animations, transitions, or dynamic data updates.
• •Poor Handling of Complex Flows: Multi-page applications and complex user flows are particularly challenging for screenshot-based tools. They struggle to stitch together the different screens and maintain state across transitions.

This results in generated code that is often:

• •Bloated: Containing unnecessary elements and redundant logic.
• •Brittle: Prone to breaking with minor UI changes.
• •Difficult to Maintain: Requiring extensive manual refactoring.

Replay's Approach: Behavior-Driven Reconstruction#

Replay takes a fundamentally different approach. Instead of relying on static images, it analyzes video recordings of user interactions. This allows Replay to:

• •Understand User Intent: By observing the sequence of actions, Replay can infer the user's goals and the underlying logic of the application.
• •Capture Dynamic Behavior: Replay can capture animations, transitions, and dynamic data updates, resulting in more accurate and complete code.
• •Generate Multi-Page Applications: Replay can seamlessly reconstruct entire user flows, including navigation between pages and state management.

This "Behavior-Driven Reconstruction" leads to cleaner, more maintainable code that requires significantly less manual cleanup.

Feature Comparison: Replay vs Cursor#

Let's compare the key features of Replay and Cursor:

📝 Note: Cursor offers powerful code completion and suggestion features within the IDE, which are complementary to Replay's code generation capabilities. The comparison focuses on the core code generation aspects.

A Practical Example: Reconstructing a Simple Task List#

Let's illustrate the difference with a simple example: reconstructing a task list application. Imagine a user recording a video of themselves:

1. •Adding a new task ("Buy groceries")
2. •Marking the task as complete
3. •Deleting the task

With Cursor, you would likely need to provide screenshots of each state (empty list, task added, task completed, task deleted). The generated code might look something like this (simplified for brevity):

javascript
// Generated by Cursor (Screenshot-Based) - Requires significant cleanup

import React, { useState } from 'react';

function TaskList() {
  const [tasks, setTasks] = useState([]); // Initial state from screenshot 1

  // Event handlers based on visual cues - INACCURATE
  const addTask = () => { /* ... complex logic based on screenshot 2 ... */ };
  const completeTask = () => { /* ... complex logic based on screenshot 3 ... */ };
  const deleteTask = () => { /* ... complex logic based on screenshot 4 ... */ };

  return (
    <div>
      {/* UI elements based on screenshots */}
      <button onClick={addTask}>Add Task</button>
      {tasks.map(task => (
        <div>
          <input type="checkbox" onChange={completeTask} />
          <span>{task}</span>
          <button onClick={deleteTask}>Delete</button>
        </div>
      ))}
    </div>
  );
}

export default TaskList;

Notice how the

, , and functions are placeholders. Cursor can only infer that these actions exist, but not how they should be implemented. It struggles to connect the button clicks to the actual data manipulation. This code requires significant manual intervention to implement the correct logic.

Now, let's see how Replay handles the same video:

typescript
// Generated by Replay (Video-Based) - Clean and functional

import React, { useState } from 'react';

function TaskList() {
  const [tasks, setTasks] = useState([]);

  const addTask = (newTask: string) => {
    setTasks([...tasks, newTask]);
  };

  const completeTask = (index: number) => {
    const updatedTasks = [...tasks];
    updatedTasks[index] = { ...updatedTasks[index], completed: true };
    setTasks(updatedTasks);
  };

  const deleteTask = (index: number) => {
    const updatedTasks = tasks.filter((_, i) => i !== index);
    setTasks(updatedTasks);
  };

  return (
    <div>
      <input type="text" id="newTask" />
      <button onClick={() => addTask(document.getElementById('newTask').value)}>Add Task</button>
      {tasks.map((task, index) => (
        <div key={index}>
          <input type="checkbox" checked={task.completed} onChange={() => completeTask(index)} />
          <span>{task.text}</span>
          <button onClick={() => deleteTask(index)}>Delete</button>
        </div>
      ))}
    </div>
  );
}

export default TaskList;

Replay, by analyzing the video, understands the relationship between the button clicks and the data updates. It correctly implements the

, , and functions, resulting in a fully functional task list application without significant manual cleanup. It observes the user typing in the input field and correctly associates that input with the task being added.

Step-by-Step: Generating Code with Replay#

Here's a simplified guide to generating code with Replay:

Step 1: Record Your UI Flow#

Use any screen recording tool to capture the desired user flow. Ensure clear and concise interactions.

Step 2: Upload to Replay#

Upload the video to the Replay platform.

Step 3: Review and Refine#

Replay will automatically generate the code. Review the code and make any necessary adjustments.

Step 4: Integrate into Your Project#

Copy and paste the generated code into your project.

💡 Pro Tip: For best results, speak clearly while recording the video. Mentioning the names of elements or actions can help Replay better understand your intent. For instance, saying "Now I'm adding a task" before typing in the input field provides valuable context.

Replay's Key Advantages:#

• •Reduced Development Time: Generates functional code faster, minimizing manual coding effort.
• •Improved Code Quality: Produces cleaner, more maintainable code.
• •Enhanced Collaboration: Facilitates communication between designers and developers by providing a shared understanding of user flows.
• •Faster Prototyping: Quickly create interactive prototypes from video recordings.

⚠️ Warning: While Replay significantly reduces manual coding, it's still important to review and test the generated code thoroughly. AI-generated code is not a replacement for human expertise.

Replay's Secret Sauce: Gemini Integration#

Replay leverages the power of Google's Gemini models to understand the nuances of human behavior and translate it into working code. Gemini's advanced video understanding capabilities allow Replay to:

• •Identify UI Elements: Accurately detect buttons, input fields, and other interactive elements.
• •Recognize User Actions: Understand clicks, taps, swipes, and other gestures.
• •Infer Data Flow: Track the flow of data between different UI elements.
• •Generate Semantic Code: Produce code that is not only functional but also semantically meaningful.

This deep integration with Gemini is what sets Replay apart from traditional screenshot-to-code tools.

Frequently Asked Questions#

Is Replay free to use?#

Replay offers a free tier with limited usage. Paid plans are available for more extensive use and access to advanced features.

How is Replay different from v0.dev?#

v0.dev primarily relies on text prompts and component libraries to generate UI code. Replay, on the other hand, uses video input to understand user behavior and reconstruct working UI from screen recordings. Replay focuses on capturing existing UI and workflows, while v0.dev focuses on generating new UI from scratch.

What frameworks does Replay support?#

Replay currently supports React and Vue.js, with plans to add support for other popular frameworks in the future.

Can Replay handle complex animations and transitions?#

Yes, Replay can capture and reconstruct animations and transitions from video recordings.

Does Replay integrate with other tools?#

Replay integrates with Supabase for data persistence and offers APIs for integration with other development tools.

---

Ready to try behavior-driven code generation? Get started with Replay - transform any video into working code in seconds.