Dribble Sync

Login Details

email - a@a.com password - password

Inspiration

Drinking culture is a huge part of university in the UK, and my experience has been no different. The idea for DribbleSync was born like all the best ideas, in the pub with a few friends. Using a phone stopwatch to time my friend drinking a pint got me thinking - what if we could see all our data on what we drink, when we drink it, how quickly we drink throughout the night etc. the next morning. I currently work for an aerospace company mostly working in data analytics, try as I might even off the clock I can't stop thinking about Excel spreadsheets (for better or worse). DribbleSync is the product of UK university culture meeting my experience and knowledge of handling, parsing, and displaying data.

What it does

The idea itself is quite simple, users can create "drinking sessions" and begin to add drinks as they order them. Once you add a drink, the timer starts. When you finish the drink the timer is stopped and the drink is added to your session, immediately DribbleSync starts building a graph showing each drink throughout the night, when you drank it, what drink it was, and how long it took to drink. The potential here for what data is shared and displayed is endless.

How we built it

Technically, DribbleSync is nice and straightforward. A react front end hooked up to a Supabase backend hosted on Netlify (and of course created in Bolt.new). Timing is handled locally, and edge functions handle most of the communication with Supabase to keep it easy from a development point of view to make changes to how we handle data being sent back and forth.

Challenges we ran into

A couple of the assumptions that Bolt.new made caused us problems during development, for example originally we would send a date stamp for when drinks were started and finished and this began creating some weird situations where times didn't line up. Apparently I drank a beer in -59 seconds at one point! The real big learning moment for this project was how to write clever prompts with Bolt.new.

Accomplishments that we're proud of

I am really proud of how it looks, it's exactly how I envisioned it - minimalistic, straightforward and does exactly what it's meant to. Making interesting and useful graphs from huge data sets is my day job, and it felt good to get to flex that bit of my experience in a project of my own.

What we learned

Truthly, I wasn't necessarily pro-AI development prior to this project. I've always been a strong programmer and sort of didn't see the point of using AI, but after this project I have to put my hands up and admit I was wrong - it simply is so much faster than me at the easy bits, and for the hard bits it can read documentation so much quicker that once you get the hang of prompting properly, its such a fantastic tool for development.

What's next for Dribble Sync

2 big things next. Mobile app - this is huge because its such an accessibility feature for users and makes it incredibly easy to use in a pub/bar setting. I geniunely think there is huge potential for this project because of the nature of UK drinking culture and the fact that you have a new intake of potential users every year joining university, and I think a mobile app is how we capture that. Secondly, a "multiplayer" mode where you can see your friend's drinks in real time would be a fantastic addition.

Built With

• netlify
• react
• supabase