AI Friendliness Scanner

The AI Friendliness Scanner is the first tool to optimize websites for AI discovery. Our 9-factor analysis gives you actionable insights to make your content stand out to AI search engines and LLMs.

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AI Friendliness Scanner - My Project Story

What Inspired Me

I saw that Bolt.new was having a hackathon and I started brainstorming ideas. Then I realized that the best ideas usually solve questions people are actively asking. Lately, everyone's been asking us the same thing: "How do we make our site friendly for AI?"

As people use AI tools more often in place of search engines, it's becoming clear that website owners need to understand how AI bots view their website.

So I built a tool to help anyone make their website easier for AI to understand using Bolt.new.

What I Learned

Building this project taught me how fast you can build a modern website or web app with Bolt.new. I was impressed with how quick the process was. I plan on using it to build out a paid version of this tool in the near future.

How I Built It

This project is a perfect example of what's possible in the AI era. I used:

  • Claude (Anthropic), ChatGPT and Perplexity for brainstorming the 9-factor analysis system and generating the scoring logic
  • bolt.new for rapid prototyping and development
  • Modern web technologies to create a fast, responsive scanning tool

The development process was incredible. What would have taken me months of traditional coding happened in days. I could iterate quickly, test ideas immediately, and focus on the core value proposition instead of getting bogged down in technical implementation.

The 9-factor scoring system analyzes:

  1. Schema Markup
  2. Heading Hierarchy
  3. List Structure
  4. Readability
  5. Front-loaded Information
  6. Active Voice Usage
  7. FAQ Format
  8. Clear Definitions
  9. AI Bot Access Configuration

It connects to Supabase to store the IP address of people who use the site in order to limit them to 10 URL scans a day. Every day the limit is reset.

Challenges I Faced

The biggest challenge? I had never used bolt.new before. Learning a new platform while building a complex project was definitely a challenge.

The biggest issue I faced was at deployment. I burned through over 10 million credits trying to deploy to Netlify, then spent even more credits fixing all the build errors that only showed up once it was actually deployed.

Lesson learned: If I had to do it over again, I would have deployed the app much earlier in the process to work out the bugs incrementally, rather than dealing with everything all at once at the end.

Other challenges included:

  • Once the app was deployed to netifly there were resource limitations that broke the code that didn't exist in my local environment (timeouts, and memory limits). I had to spend a lot of time debugging and fixing those once it was deployed to netifly
  • Defining what "AI-friendly" actually means (there's no established standard yet)
  • Building a reliable web scraping system that works across different site architectures
  • Creating a scoring algorithm that's both accurate and actionable
  • Resisting scope creep and staying focused on the MVP

The Result

The AI Friendliness Scanner is live at manty.ai with over 10 free scans per day. It's the first tool I know of that is specifically designed for the AI era, giving businesses a clear roadmap to optimize their content for AI discovery.

What makes me proudest: I went from idea to working product in the time it used to take just to plan a project. That's the power of AI-assisted development, and it's exactly why tools like bolt.new are game-changers for builders like me.

The future of content discovery is AI-driven. My tool helps businesses be ready for that future, today.

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