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Show HN: The App I Built to Help Manage My Diabetes

(apps.apple.com)
184 points yeatsy | 1 comments | 18 Nov 24 00:07 UTC | HN request time: 0.203s | source

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

1. siquick ◴[19 Nov 24 00:29 UTC] No.42178874[source]▶
First up - awesome work.

Having been through the year long build of a similar app for another health condition here’s some thoughts focusing on the GenAI side of things:

- What’s the source of the responses? Is this a RAG system or straight-to-LLM?? We have an ever-growing huge repo of domain expert written content which is the source for our RAG system. It’s far easier to control potential misinformation with a well set up RAG and some tight prompting/guardrails.

- What verification do you have that the responses are correct? We have a group of 50 highly experienced experts in the field who constantly vet the responses to our synthetic set questions and it was eye opening how often our “looks good to me” analysis was off at the beginning.

- The main reason for this questions was that your responses are going to be wrong sometimes, what legal protection do you have? Disclaimers, terms of use at absolute minimum. Who is liable if the answer is wrong? Just presume someone is going to be very upset if your response gives them bunk info.

Either way - great work.