The App I Built to Help Manage My Diabetes

Hacker News

Hi HN, I’m Joshua, a student, and I’m excited (and a little nervous) to share something deeply personal that I’ve been working on: Islet, my diabetes management app powered by GPT-4o-mini. It’s now on the App Store, but I want to be upfront—it’s still very much in its early stages, with a lot more to go. I was diagnosed with Type 1 diabetes while rowing competitively, and that moment changed everything. It wasn’t just the practical challenges of managing insulin, carb counts, and blood sugars; it fundamentally shifted how I see myself and the world. It forced me to slow down, prioritise my health, and take control in ways I never had to before. My outlook on life became more focused on resilience, adaptability, and finding solutions to problems that truly matter. This app started as a pet project over the summer, a way to see what I could create using ChatGPT and explore the potential of LLMs to help with real-world challenges. At first, it was just about making my own diabetes management easier—understanding patterns in blood sugars, planning meals, and adjusting routines. But as I worked on it, I realised it could do more. Right now, Islet offers personalised meal suggestions, tracks activity, and provides basic insights based on the data you enter. It’s far from complete. Even so, the process of building Islet has already taught me so much about how powerful AI can be in creating personal, meaningful tools. This project is deeply tied to how my diagnosis changed me. It’s about more than managing diabetes, it’s about showing how anyone, even a student experimenting over the summer, can use AI to potentially solve real, personal problems. I believe tools like LLMs have the power to democratise solutions for all, making life just a bit easier for all of us. If you’re curious, you can check it out here: https://apps.apple.com/gb/app/islet-diabetes/id6453168642 . I’d love to hear your thoughts what works, what doesn’t, and what features you think would make it better. Your input could help shape the next steps for Islet. Thanks for reading ! joshua

Visit product View on Hacker NewsNov 18, 2024

Share card

Actual performance

185points

73comments

Made the leaderboard

Launch Intel predictions

Analyze your own launch →

Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

97%97% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: apple, apps, chatgpt · Missing: mac, agents, macos

78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: personal, apps, way · Missing: mobile apps, ios, entrepreneurs

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, ide, io · Missing: https docs, just released, exist

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

8%8% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

Neatter App Built for Berlin Hackday56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Neatter App Built for Berlin Hackday

Hacker News4

Show HN - Gifft, My first app. Built with Phonegap and AngularJS52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Show HN - Gifft, My first app. Built with Phonegap and AngularJS

Hacker News5

an app I built to help you find great beer55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

an app I built to help you find great beer

Hacker News43

Forest Requirements, an iPad app I built to manage requirements38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Forest Requirements, an iPad app I built to manage requirements

Hacker News1

The app I built to manage my anxiety39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The app I built to manage my anxiety

Hacker News3

Yoda, osx app built using Reactjs and Electron48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Yoda, osx app built using Reactjs and Electron

Hacker News2

Dwellable – The app I built after waiving home inspection during Covid35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Dwellable – The app I built after waiving home inspection during Covid

Hacker News5

Hypermedia-driven app built with Htmx and C++53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Hypermedia-driven app built with Htmx and C++

Hacker News1

A library app built with NextJS, Prisma 2 and Apollo – explained51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A library app built with NextJS, Prisma 2 and Apollo – explained

Hacker News12

My iBeacon app built in a few hours55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My iBeacon app built in a few hours

Hacker News4

Browse all products Analyze your launch