My

My 1st mobile app- A parasitic,anonymous,remixable img app for android

Hacker News

My 1st mobile app- A parasitic,anonymous,remixable img app for android

https://play.google.com/store/apps/details?id=com.daveganly.yarrly Hi, this is Yarrly - my first android app, backed up server side by a mongo & node.js backend. It’s a two-panel image generator, and quite a fun experiment in a no-login (‘anonymous’) app. You generate two panel images using photos or gallery pics, and add text, then it’s uploaded to Yarrly.com - creating an instagram-like link. For example you create http://yarrly.com/y/4hhs6ryyq73da533d, then android intents mean that if you open that link on a device that has Yarrly, you can view the image, but then also remix it. Remixing downloads the component parts of the yarrly, allowing the new user to edit them, add new images or text, and upload again. This means you can create chains, like this: http://yarrly.com/c/4hhs6ryyq73da533d So part of the interesting idea is that it’s anonymous, so the links are as private as you make them. Share the link on email, and you can have a nice two way conversation with a friend. Share it on twitter, and anyone who finds the link can remix your Yarrly. That’s what I mean by ‘parasitic’ - it doesn’t have any concept of users, friends or anything else; it relies on being shared on other platforms to spread. Why was it made? I needed to learn mobile development and android seemed a bigger challenge than iOS - also a fun challenge to try something properly in nodejs and mongo - my last project (http://vvx.io/) was a ruby/rails web app sitting on postgresql. Why no holo theme? Meh, wanted to do something more unique and playful. This is an experiment more than anything, so why not pirate theme? Who made it? I did the code, my girlfriend came up with the idea and the fantastic design. Everything was arrived at through experimentation and discussion.

Share card

Actual performance

31points
16comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: para, ios · Missing: supports, reddit linkedin, podcasting
92%92% 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: google, apps, user · Missing: mac, agents, macos
65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios, apps, google · Missing: mobile apps, personal, entrepreneurs
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
32%32% 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 · Strong signals: arr · Missing: mrr, revenue, profit
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

da
dal-app-148%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

a mobile app

TrustMRR267$3,759/moMobile Apps
Mo
Mobile App Grader42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Mobile App Grader

Hacker News6
Mo
Mobile App Automizer42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Mobile App Automizer

Hacker News22
Th
The Crowdtilt Mobile App42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The Crowdtilt Mobile App

Hacker News35
Satsport
Satsport34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

satsport mobile app

Indie Hackers
A
A metric-tracking, mobile app43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A metric-tracking, mobile app

Hacker News1
Dirt Slingin Tech
Dirt Slingin Tech63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

DST Mobile App

Indie Hackers1$500/moai
Mobile App Scanner
Mobile App Scanner46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Test security and privacy of any iOS or Android mobile app

Indie Hackerscommitment-side-project
Bu
Building a Mobile App39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Building a Mobile App

Hacker News1
PKUP
PKUP52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Mobile app defining the market of Cargoshare

Indie Hackers1apis