Replay vs Cursor for UI Forms: Which AI Creates Better Frontend Input Validation from Video?

TL;DR: Replay reconstructs UI forms from video, leveraging behavior analysis for superior input validation compared to Cursor's screenshot-based approach, resulting in more robust and user-friendly frontend code.

Recreating UI forms with accurate input validation is a pain. Traditional screenshot-to-code tools often miss critical behavioral nuances, leading to fragile and incomplete implementations. But what if you could simply show the tool how the form is used? That's the power of video-to-code engines. Let's dive into a head-to-head comparison: Replay versus Cursor, specifically focusing on how each handles input validation.

The Challenge: Intelligent Form Reconstruction#

Building forms that not only look right but also behave correctly is a common frontend development bottleneck. Consider a simple sign-up form. You need to ensure:

• •Email addresses are valid.
• •Passwords meet complexity requirements.
• •Required fields are filled.
• •Error messages are displayed appropriately.

Screenshot-to-code tools struggle with these dynamic aspects because they only see the static visual representation. They lack the context of user interactions and the underlying logic.

Replay: Behavior-Driven Reconstruction#

Replay takes a different approach. It analyzes video recordings of user interactions with a UI form. By observing how a user interacts with the form – what they type, where they click, and how the UI responds – Replay can infer the intended behavior and generate code that accurately reflects it. This "Behavior-Driven Reconstruction" is the key to Replay's superior form handling capabilities.

Cursor: Screenshot-Based Generation#

Cursor, like many other AI-powered code generation tools, primarily relies on screenshots as input. While it can generate impressive UI layouts, it often falls short when it comes to capturing the dynamic behavior of forms, particularly input validation. It may guess at basic validation rules, but it lacks the insight to create robust and context-aware logic.

Head-to-Head Comparison: Input Validation#

Let's examine a concrete example. Imagine a video recording of a user filling out a form with a password field that requires at least 8 characters, one uppercase letter, and one number.

Cursor might generate basic HTML input fields with some client-side validation, but it likely won't capture the specific password requirements. Replay, on the other hand, would observe the user triggering validation errors by entering invalid passwords and generate code that enforces the correct rules, including displaying appropriate error messages.

Code Example: Password Validation#

Here's an example of the type of code Replay might generate for password validation, using React and a validation library like

:

typescript
import { useState } from 'react';
import { z } from 'zod';

const passwordSchema = z.string()
  .min(8, { message: "Must be at least 8 characters" })
  .regex(/[A-Z]/, { message: "Must contain at least one uppercase letter" })
  .regex(/[0-9]/, { message: "Must contain at least one number" });

const SignupForm = () => {
  const [password, setPassword] = useState('');
  const [passwordError, setPasswordError] = useState('');

  const handlePasswordChange = (e: React.ChangeEvent<HTMLInputElement>) => {
    setPassword(e.target.value);
    try {
      passwordSchema.parse(e.target.value);
      setPasswordError('');
    } catch (error: any) {
      setPasswordError(error.errors[0].message);
    }
  };

  return (
    <div>
      <label htmlFor="password">Password:</label>
      <input
        type="password"
        id="password"
        value={password}
        onChange={handlePasswordChange}
      />
      {passwordError && <p className="error">{passwordError}</p>}
    </div>
  );
};

export default SignupForm;

This code snippet demonstrates how Replay can generate robust validation logic based on observed behavior. Cursor, lacking this behavioral insight, would likely produce a much simpler and less effective implementation.

Implementing Input Validation with Replay: A Step-by-Step Guide#

Here's how you can leverage Replay to generate UI forms with intelligent input validation:

Step 1: Record User Interaction#

Record a video of yourself (or a user) interacting with the form you want to reconstruct. Make sure to demonstrate all the different scenarios, including entering invalid data to trigger validation errors. Show the happy path, and all the unhappy paths.

Step 2: Upload to Replay#

Upload the video to Replay. The AI engine will analyze the video and identify the UI elements, user interactions, and underlying behavior.

Step 3: Review and Refine#

Review the generated code and make any necessary adjustments. Replay provides a user-friendly interface for editing the code and fine-tuning the behavior.

Step 4: Integrate into Your Project#

Copy the generated code into your project and integrate it with your existing codebase.

💡 Pro Tip: For complex forms, consider recording multiple videos, each focusing on a specific aspect of the form's behavior. This can improve the accuracy of the reconstruction.

Beyond Basic Validation: Advanced Scenarios#

Replay's behavior-driven approach shines in more complex scenarios, such as:

• •Conditional Validation: Validation rules that depend on the values of other fields. For example, requiring a confirmation password only if the user chooses a specific account type.
• •Dynamic Error Messages: Error messages that change based on the specific error condition.
• •Asynchronous Validation: Validation that requires making a request to a server, such as checking if a username is available.

Cursor and other screenshot-based tools struggle to handle these scenarios effectively, often requiring significant manual coding to implement the necessary logic. Replay, by understanding the user's intent and the form's behavior, can generate code that accurately reflects these complex requirements.

📝 Note: Replay's integration with Supabase allows you to easily connect your forms to a backend database and implement server-side validation.

The Benefits of Behavior-Driven Form Reconstruction#

• •Reduced Development Time: Replay automates the tedious task of manually coding form validation logic.
• •Improved Code Quality: The generated code is more robust and less prone to errors.
• •Enhanced User Experience: Forms behave as expected, providing a smoother and more intuitive user experience.
• •Increased Accuracy: Captures the nuances of user behavior for precise form logic.

⚠️ Warning: While Replay significantly accelerates development, always thoroughly test the generated code to ensure it meets your specific requirements.

Comparison Summary#

Frequently Asked Questions#

Is Replay free to use?#

Replay offers a free tier with limited usage, allowing you to explore its capabilities. Paid plans are available for higher usage and access to advanced features.

How is Replay different from v0.dev?#

v0.dev primarily focuses on generating UI components from text prompts. Replay, on the other hand, analyzes video recordings of user interactions to reconstruct entire UIs, including form behavior and input validation. Replay captures intent where v0.dev generates from prompts.

What frameworks does Replay support?#

Replay currently supports React, with plans to expand to other popular frameworks in the future.

Can I use Replay to reconstruct existing forms?#

Yes, you can record a video of yourself interacting with an existing form and use Replay to generate the corresponding code. This can be a great way to refactor or modernize legacy forms.

Does Replay support custom validation rules?#

Yes, Replay allows you to customize the generated validation rules to meet your specific requirements. You can edit the code directly or use Replay's visual editor to modify the behavior.

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