FakeOut

Challenge your AI-image detection skills in our daily quiz!

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Inspiration

The idea for FakeOut came when I started encountering more and more AI videos and images that made me second-guess whether they were AI-generated or real. If I struggle to recognize these, how can the rest of the reddit community deal with this? How can they identify which images are fake, or at least develop an intuition for it and look out for features that might make them question whether the image they are seeing is real?

What it does

FakeOut is a daily game that challenges users to identify AI-generated images when paired directly against a similar but real image. In five rounds, the game shows themed pairs of images. After each guess, the user receives feedback in the form of a percentage score indicating how many redditors guessed that pairing correctly. They can also view the prompt that was used to generate the fake image or video to learn what to look out for — what the model might have failed to reproduce correctly even though the information was included in the prompt. We also encourage players to challenge their friends or family to play along, compare results, or discuss their findings on Reddit — sharing how they figured out which ones were fake.

We also enable the community to submit 'themes' for the upcoming games as well as voting for them. This way, the community can decide what they want the AI see try to replicate next.

How we built it

As a solo developer with limited time and money, I was amazed to see that the Reddit team has published a GitHub template that already has integration with AI IDEs like cursor and kiro. I prefer to use VSCode with Claude Code integration but could easily reuse these template files as well as the MCP connection definition. Then I went at it. Almost every day after work, I sat down a couple of hours to get this game implemented.

The frontend was implemented in React using Tailwind CSS for styling, along with some custom CSS.

The automated lambdas are coded in Python and typescript and mainly trigger Gemini API endpoints. The automation works as follows:

  • We scrape images from a license-free library.
  • We call the Gemini 3 API multimodal model for meta-prompting, letting it generate a prompt based on what it sees in the image and explaining it as thoroughly as possible.
  • We send this detailed prompt to the Gemini 3 API, invoking the latest Nano Banana Pro for image generation.

Challenges we ran into

Working on this project alongside a 9-to-5 job was definitely the biggest challenge. My passion for programming and for advancing AI literacy helped me overcome it, but it was definitely a stretch.

It was also difficult to find high-quality license-free images in an automated way that would make the game interesting for users. In the early stages, many scraped images were such low quality that the difference in resolution or lighting conditions was a dead giveaway — making it too easy for players to spot which video was AI-generated and which wasn’t.

Accomplishments that we're proud of

I’m really proud that I was able to bring this project to life in such a limited time, and that people were genuinely interested in it. I'm also prooud that I brought the community voting feature for the upcoming themes to life, since I feel like that is a really fun and engaging feature that might bring the user back in upcoming days.

I’m a big fan of AI and use it for several hours every day, but I think it’s crucial for us to foster AI literacy among everyone. Seeing that my small side project could contribute to that for some people made me really proud.

What we learned

Working in a more traditional software development job, it was fascinating to see how AI enables developers to quickly produce MVPs, use agents in daily workflows to accelerate development by 10x, and still achieve relatively high-quality results.

Personally, I learned a lot about modern software development — including what tools and frameworks are popular today, the importance of using agents during development, the impact MCP servers can have when set up with the right tools, and the everyday life of solo developers. I also discovered how plug-and-play it is to integrate with Reddit's Developer tools and how quickly ambitious visions can come to life nowadays.

What's next for FakeOut

Depending on the interest this project receives, I would love to keep working on it. I’d like to implement new features. I really want to try to hook some users and try to reach the Tier 1 goal for the Reddit developer fund.

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