Meal planning app I built after losing 50kg myself in 2022

Hacker News

1500cals is a calorie and excercise tracking tool that I built after losing 50kg myself in 2022 through simply watching what I ate and starting to exercise. The main "trick" I uncovered is simply to plan meals ahead. It sounds boring, it sounds annoying, but really its such a tiny effort for such outsized and life changing rewards that it should be a no-brainer. The existing tools I found were more focused on tracking after eating which is great in terms of capturing data and measuring over time, but I found really didn’t help me with locking in a routine. I wanted to fix this and bring some of this planning side along with tracking into an easy to use app. This is 1500cals!

Visit product View on Hacker NewsDec 27, 2023

Share card

Actual performance

11points

4comments

Made the leaderboard

Launch Intel predictions

Analyze your own launch →

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

70%70% 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: tiny · Missing: mac, agents, macos

55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: reward · 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

Suprvegan40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Vegan Meal Planning App

Indie Hackerscommitment-side-project

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

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

MyMeal.io46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your meal planning app.

Indie Hackerscommitment-side-project

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

Tofu – Meal planning kept simple37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tofu – Meal planning kept simple

Hacker News3

Browse all products Analyze your launch