100 Interest Score
19 Discussions
0.19 Engagement
Nov 2023 Launched
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Get actionable advice on how to best style your hair and what three other haircuts might suit you well. Plus, get your haircut roasted.

What the Community Said

Hi PH! I made the first actionable(and quite spicy) hairstyle consultant. Is your current haircut don't you? Which one to make? How style? Upload a picture of yours. Give it around 30 seconds to review every aspect. Then Leonardo DiBarbiere and GPT-4 Vision will give you on-point advice about your hair. First, it'll give you a proper roast of your haircut. Then it will advise you on how to style your current haircut better and take care of your hair. Besides to your current haircut, it will show

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That's a cool project. Congrats on the launch : ) I loved the suggestions it made. One "wow" feature the product can have is you can show the actual cut with the selfie so that I can see how it looks in real without imagining it. And then you can sell to the hair stylists and the barbers and can have a self-sustaining business. Best wishes : )

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Congrats on the launch of Haircut and Styling Advice! 🎉 The personalized advice for haircuts and styling sounds like a game-changer. How does the AI take into account individual preferences and trends? Upvoted and looking forward to trying it out!

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@nikitattt : Congrats on the launch team, the product looks amazing.

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@nikitattt, this is amazing! You have crafted a unique service that will be of great use to those seeking out the perfect haircut and hairstyle - something we all desire at some point. A big thumbs up for a job well done!

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Frequently Asked Questions

A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.

Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.

Categories come from the product's launch tags. Most products appear in 2-3 categories. The primary category is listed first.

The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.

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