How to Create VIRAL Car Crash Videos with AI (400K+ Subs!)

Key Concepts

AI-generated video creation, no-code automation, Naden, Google V3 video model, OpenAI, HTTP request node, file.ai, viral content creation, AI automation consultant, workflow automation, form triggers, API integration, JSON data handling.

AI-Generated Video Automation: A Step-by-Step Guide

This tutorial details how to create AI-generated videos, similar to those achieving viral success on platforms like Instagram and YouTube, using no-code AI automation. The core idea is to leverage a simple form to define video parameters, then use AI to generate the video automatically.

1. Introduction and Opportunity

The video highlights the potential of AI-generated content, showcasing examples of videos with millions of views. It emphasizes that anyone can now create such content without traditional video editing skills or coding knowledge. The presenter, Zub, positions this as a significant opportunity to gain followers and monetize content.

2. Naden and Workflow Setup

The tutorial uses Naden, a no-code AI automation platform, to build the video creation workflow.

• Naden Basics: Naden is presented as a beginner-friendly platform. A 14-day free trial is mentioned.
• Workflow Trigger: The workflow starts with a "Form" trigger, which initiates the video creation process based on user input.

3. Form Creation

The tutorial explains how to create a form within Naden to collect video parameters:

• Form Elements: The form includes fields like "Car Type," "Crash Object," "Crash Site," and "Crash Style."
• Dropdown Lists: These fields use dropdown lists to provide predefined options (e.g., Lamborghini, Ferrari for "Car Type").
• Required Fields: Setting fields as "required" ensures users provide necessary information.

4. OpenAI Integration for Prompt Generation

After form submission, the workflow uses OpenAI to generate a video prompt:

• OpenAI Node: An OpenAI node is added to the workflow to interact with OpenAI's models.
• API Key: Users need an OpenAI API key, obtainable from the OpenAI website.
• Prompt Template: A specific prompt is used to instruct OpenAI to generate a cinematic video prompt suitable for Google's V3 model. The prompt emphasizes dramatic crash test scenarios.
  • Example Prompt: "Based on the inputs below generate a cinematic video prompt suitable for Google's VO3 model... focus on dramatic crash test scenario..."
• Dynamic Values: The prompt incorporates dynamic values from the form submission, ensuring the generated prompt is tailored to the user's choices.
• JSON Output: Toggling specific settings ensures the output is in JSON format.

5. Google V3 Integration via HTTP Request Node

The generated prompt is then sent to Google's V3 video model using an HTTP request node:

• HTTP Request Node: This node allows the workflow to interact with external APIs.
• File.ai API: The tutorial uses file.ai, a third-party platform, to access the V3 model.
  • Note: The presenter mentions that V3 is expensive (around $6 per 8-second video).
• API Endpoint: The HTTP request is sent to a specific file.ai endpoint for video creation.
• Authentication: Authentication is handled using generic credentials and an API key from file.ai.
• Request Body: The generated prompt is sent as a JSON payload in the request body.
  • Body Content Raw: application/json
  • JSON Structure: {"prompt": "dynamic prompt from OpenAI"}
• Items per Batch: Set to 1.
• Batch Intervals: Set to 2000 milliseconds.

6. Wait Node for Processing Time

A "Wait" node is added to the workflow to allow time for the V3 model to generate the video:

• Wait Time: The wait time is set to 5 minutes.

7. Retrieving the Generated Video

After the wait period, another HTTP request node is used to retrieve the generated video:

• Get Request: This node sends a GET request to a specific file.ai endpoint to retrieve the video URL.
• Authentication: Similar authentication as before.
• Video URL: The response from the API includes the URL of the generated video.

8. Video Usage and Monetization

The tutorial concludes by discussing how to use the generated videos:

• Social Media: The videos can be posted on platforms like TikTok, YouTube Shorts, and Instagram.
• Monetization: The presenter suggests joining his community to learn how to monetize these videos.

9. Additional Tips and Tools

• Workflow Architect GPT: A custom GPT is mentioned that can generate Naden workflows from a description. This can further streamline the automation process.
• JSON Import: Naden allows importing workflows from JSON files.

10. Conclusion

The tutorial emphasizes the massive opportunity presented by AI-generated video content. While the V3 model is expensive, the presenter argues that the high-quality, eye-catching videos are worth the investment, especially for social media marketing and monetization. The automation makes the process simple and accessible to anyone with ideas.