Copy Apps with AI: Medical Tracker

Breaking down and reproducing an app with $1M ARR in 8 months after launch

While reading about projects built by solopreneurs, I came across a nice story. It's an app called Shotsy that helps people track their medications. Since its launch, it grew to $1M ARR in 8 months and later raised $2M.

So, two questions arose for me. The first is how Shotsy managed to achieve such growth. And, of course, the second question is whether we can replicate this product without coding but with AI. Let's answer them.

In this issue:

• A breakdown of a startup’s journey from idea to market

• What key elements made Shotsy a hit

• Quick tutorial on how to leverage AI to build your own app

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From a Personal Problem to Monetizable Product

Meet Aja Beckett, today's case. She is a software engineer who worked for The Athletic and The New York Times. For a long time, she used notes to track her intake of GLP-1 medications (you may have heard of them as Ozempic) and her body's subsequent response.

At some point, she realized that using regular note-takers to log weekly injections and track progress and side effects was the wrong approach. The notes became too long and unruly. So Beckett decided to create her own product: one that would help her and people with the same problem.

It was named Shotsy and was given the following features:

• Weekly Injection Logging: Record every shot, capturing dose timing and details.

• Side Effects Tracking: Log reactions such as nausea and other symptoms to predict and manage feelings.

• Injection Site Rotation: Record of injection sites to help ensure proper rotation and minimize irritation.

• Progress Monitoring: Track changes in weight and other health metrics over time, making it easier to see progress.

The first version of the app was developed in-house. Since Beckett was still working full-time as an engineer, users of the Zepbound community (a subreddit on Reddit where people taking Ozempic share their experiences and support each other) acted as the first testers. This gave a good boost to Shotsy's first promotion.

The app saw 3,000 downloads in the first 24 hours after its debut on the App Store. And many provided detailed feedback on desired features.

Have covered how to find an audience using AI in this post.

This grassroots approach solved two potential problems:

• Trust in a marketplace wary of medical misinformation

• Product verification through direct user input

As for monetization, the founder opted for a familiar freemium model.

The free version handles basic tracking, while a $19.99/year subscription unlocks advanced analytics such as symptom correlation reports and injection site effectiveness ratings.

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Growth and Investor Attention

As the audience grew, Beckett brought in a part-time designer to make the app more enjoyable for users. A bit later, she ran into an engineer friend and gave him a demo while traveling through the airport on her way back from a conference. He asked her to connect with investors, including Underwood, Slack's former head of product.

Result: Shotsy raised $2.25M in funding to expand its marketing and grow its team. April Underwood of Adverb Ventures led the round, which was participated in by Coalition Operators, Springbank Collective, and angel investor Esther Dyson.

Here are a few reasons why Beckett's idea attracted the attention of VCs:

1. First-mover status in the GLP-1 tracking niche

2. Beckett's founder-market fit (she's both builder and user)

3. Great timing with Ozempic hype

Now that Shotsy no longer seems like such an obscure project, we can safely say it's not MOAT. Here's why.

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How To Copy Shotsy App with AI

Let's reproduce Shotsy with AI. We won't use tools that require coding skills and will rely on development with prompts.

And we will try to make the whole process take no more than 15 minutes.

Step 1. Choosing AI Tools

When creating our app, we’ll need only two tools (you can use even one): ChatGPT and Lovable.dev. The first one is optional, but you must compose a full-fledged prompt that reflects all the features and visual style of the future app.