Guide Hub

HairOver: Building in Public Masterclass

HairOver is an AI app that shows you a haircut on your own face before you get it. This hub documents building it while it's still unfolding — the screens we shipped, the math behind pricing, the distribution plan, and the parts I haven't figured out. $1M MRR is the goal, not a result. Numbers get published when they're real.

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Who this guide is for

  • Indie founders and solo developers building a consumer AI app.
  • Anyone curious how an app's pricing, unit economics and distribution are worked out before the numbers are good.
  • People who want an honest build-in-public record, including what didn't work.

1. The Idea

A saved hairstyle photo is a photo of someone else's face and hair. HairOver exists to answer one question: would you actually choose this haircut if you could see it on you first?

Why I'm Building HairOver (and Why the Goal Is $1M MRR) →

2. Building the MVP

The first version shipped as Stylora: photo → analysis → ranked style report → details → try-on on your own face. Real screenshots, and what I still can't answer about them.

What the First Version of HairOver Looked Like →

3. Launch

HairOver is live on Google Play; iOS is planned. The marketing site went from first commit to SEO-ready in 30 days — built around hairstyle search intent rather than feature pages.

Building HairOver's Landing Page: 30 Days, 29 Commits →

4. Monetization & Pricing

At roughly NPR 15 per generated image, cost decides pricing. My first model missed the app store cut and priced a $55 pack at a 2% discount. The rebuild is a plan, not a result — yet.

HairOver Pricing: What NPR 15 Per Image Does to Unit Economics →

5. Distribution

Two X accounts with different jobs — the founder explains, the product demonstrates — plus SEO, creators, and UGC experiments. The plan is published before its results, on purpose.

My 30-Day X Plan for HairOver: Two Accounts, One Funnel →

6. Growth

Activation, retention, conversion. The metric that matters most right now is first generation rate: how many people who upload a photo reach a look they care about. Numbers get published here once they're real.

HairOver Growth: The Funnel I'm Measuring Before I Have the Numbers →

7. Founder Lessons & Mistakes

Rebuilding a landing page four times before it had traffic. Forgetting the platform's cut. Pre-writing posts for events that hadn't happened. Every lesson here is tied to something that actually happened.

Things I Got Wrong Building HairOver (So Far) →

8. The $1M MRR Journey

$0 → $100 → $1K → $10K → $100K → $1M. Each milestone gets documented when it's reached — and until then, it's written as a target and a hypothesis, never as an achievement.

The Math Behind HairOver's $1M MRR Goal →

Frequently asked questions

What is HairOver?

HairOver is an AI app that shows you a new haircut or hairstyle on a photo of your own face before you get it cut, so you can try styles without the risk.

Is $1M MRR a real result?

No. It's the goal this case study is working toward. Real numbers are published here when they exist, and the gap between the goal and the current state is part of the story.

What is build in public?

Sharing the work of building a product as it happens: decisions, numbers, mistakes and progress. It builds an audience and accountability, at the cost of showing things before they look good.

How is an AI app priced?

Start from what each generation costs you in model and infrastructure fees, then price so a typical user's usage leaves a healthy margin. The monetization chapter walks through HairOver's own maths.

Contact

Get in Touch

Want to call me? book a call and I'll respond in the available time slot. I will ignore all soliciting.