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Build a viral AI-powered mobile app that achieves millions of downloads

Entrepreneurs, developers, and product builders interested in creating consumer AI apps

7 months from concept to launch

What Success Looks Like

50M+ downloads in first 3 months, top app store rankings, organic viral growth without marketing spend, sustainable subscription revenue

Steps to Execute

1

Monitor AI research circles for new models going viral among technical users

2

Identify models that are powerful but difficult for laypeople to access

3

Study successful precedents in similar app categories

4

Design the simplest possible user interface (4 screens max)

5

Choose 15 carefully curated templates/options that maximize shareability

6

Build extremely fast inference (pay specialists $3K/day if needed)

7

Launch with zero marketing budget, rely on viral mechanics

8

Add monetization only after achieving significant scale

Checklist

Can a 5-year-old understand how to use the app?
Would users naturally want to share the output?
Does the app solve the accessibility problem of a viral AI model?
Is the content creation process under 30 seconds?
Are you copying proven viral mechanics from successful apps?
Do you have infrastructure to handle viral load?

Inputs Needed

  • Identified viral AI model from research community
  • Analysis of successful competitor apps
  • Technical team capable of model optimization
  • Cloud infrastructure budget for inference
  • Understanding of target platform algorithms (TikTok, Instagram)

Outputs

  • Mobile app with viral content creation loop
  • Optimized AI model for fast inference
  • Curated template library for maximum engagement
  • Organic user acquisition through sharing

Example

Ben identified first-order motion model going viral in Discord communities but requiring Google Colab to use. He copied Reface's successful face-swap app structure, applied it to the new model, and created Wombo - a 4-screen app that let anyone create singing avatars, resulting in 100M+ downloads.

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