Tres Cosas - a fun way to be more productive

Hacker News

Hey all, I was struggling with a few things after the pandemic: losing a few pounds, reviving friendships, too much social media, and not creating new fun software projects for myself. One of the things that helped a bunch was inspiration from Ali Abdaal’s book Feel Good Productivity to think about doing a few daily side quests. Side quests (in my words) being tasks that really don’t matter. They’re just fun. No one is going to get in trouble or lose their job if they don’t do them. They aren’t my todo lists or work backlog. They’re just incremental things that take a few minutes of time and cause zero stress. They aren’t goals. They don’t have success criteria other than “done”. It’s “spend 5 minutes looking up on Yelp a place with less saturated fat”. It’s not “do p90x”. It’s not “have lunch with Adam”; it’s “text Adam about lunch”. If he texts back, great. If he doesn’t, oh well. My side quest is done. Was just using a note for my side quests which works fine but thought it would be more fun to make an app tracking my side quest streaks and use it to celebrate the experience. My daughter and I named it Tres Cosas. (For 3 things. We have some ridiculous Duolingo Spanish streak :) ) and it’s on the iOS App Store. https://apps.apple.com/us/app/tres-cosas/id6479173827 It’s my first solo iOS release. So I have plenty of questions for you all about what you’d improve or do next with it. Please share how you’ve built projects like these and what worked and didn’t. And does Tres Cosas even seem like something you’d use? Would love to hear from you.

Visit product View on Hacker NewsMar 26, 2024

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

89%89% 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, new · Missing: mac, agents, macos

82%82% 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, way · Missing: mobile apps, personal, entrepreneurs

48%48% predicted probability of success on TrustMRR, 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

47%47% 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

42%42% 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 · Missing: web3, chat, crypto

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

Correct prediction on native model

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