HotDog Training App

Inspiration

Our journey started with our own dog, a 4-year-old Cockapoo named Momo, who is quite reactive. As a couple, we're both coders, but we had never built a mobile app before. Life with Momo showed us firsthand how chaotic and overwhelming managing a reactive dog can be. We wanted to create a tool to make this process more manageable and less stressful. When we came across the bolt.new hackathon, we saw the perfect opportunity to use our React skills with Expo to build an app that could help us, and hopefully many others, track goals and training for their reactive pups.

What it does

HotDog provides owners of reactive dogs with simple tools to stay consistent, track meaningful progress, and log each training session effortlessly. It's designed to bring structure, reflection, and support to the training process, helping owners keep showing up, even on the tough days.

Key Features:

Goal Setting: Set custom goals that are realistic and make sense for your specific dog and training needs.

Detailed Logging: Easily log triggers, wins, and other environmental factors that affect each training session.

AI-Powered Audio Logs: Record quick audio notes during or after a session and receive AI-generated summaries, making it easy to capture insights without cumbersome typing.

Progress Sharing: Share your dog’s journey and progress reports with trainers, veterinarians, or family members to keep everyone on the same page.

Progress Visualization: Look back at your training history to see clear, tangible evidence of how far you and your dog have come.

How we built it

We developed HotDog using a modern tech stack and a thoughtful, flexible design process. Our strategy involved physically whiteboarding key user flows, such as the onboarding screens you can see in our dev.to post, to map out the user experience before writing code.

The application was built on Expo and bootstrapped with bolt.new. This proved to be a super effective combination, as we also had bolt.new design several iterations of our components. The flexibility of this setup even allowed us to continue coding while on the go- https://x.com/ChrisLally/status/1934974891167719562 . For our backend and database needs, we utilized Supabase, and we integrated RevenueCat to handle in-app subscriptions. A core feature, our in-app AI-powered summaries, is powered by the Google Gemini Flash 2.5 model.

Challenges we ran into

One of the biggest hurdles we faced was the app store submission process. It was a significant challenge that required persistence and multiple revisions, taking us over four attempts before our app was finally approved and published.

Accomplishments that we're proud of

We're incredibly proud of the user-centric approach we took from the very beginning. We conducted in-depth interviews with professional dog trainers and dedicated owners to deeply understand their workflows. Reddit and Facebook groups were also great sources of feedback, and some of these online conversations led to calls and even in-person coffee meetings here in Boston. This research was invaluable.

A major accomplishment was seeing this research translate into a product that people wanted to use. We had a total of 15 beta users—many of whom were the trainers and owners we initially connected with—actively using HotDog through TestFlight while it was still in beta, providing us with crucial feedback.

What we learned

This project was a huge learning experience for us, as it was our first time building a mobile app. Thankfully, our prior experience with Next.js made the transition to React Native using Expo surprisingly smooth. The initial setup from bolt.new provided a great foundation, and we put a lot of thought into planning our first prompts, as we shared in our article. This hackathon pushed us to learn the entire app development lifecycle—from initial setup to app store submission. The community on Discord was also incredibly helpful, providing specific feedback that helped us improve, like pointing out that we needed to update the bolt.new badge background to a darker color to comply with the rules. As a thank you, we open-sourced our Expo badge for the community to use, which you can find here - https://x.com/ChrisLally/status/1939517333673832535 . It was a journey from a personal need to a public product.

What's next for HotDog Training App

We are committed to the continued growth of HotDog based on user feedback and our own vision. Our immediate plans involve enhancing the AI capabilities to be more proactive, such as suggesting personalized training goals for users based on their logs.

We also plan to build out more community-focused features, allowing users to connect with and support one another. We've already started exploring this by using AI to help moderate community content. Our goal is to foster a safe and encouraging space for owners of reactive dogs.

We documented our entire building process publicly on dev.to, and we plan to continue this transparent and iterative approach as we add new features and improve the app. You can follow our journey here: https://dev.to/anamaharjan/follow-as-we-build-the-hotdog-app-with-boltnew-your-dogs-progress-journal-16no

Built With

• bolt
• expo.io
• revenuecat
• supabase