Mi

Micro – apps without ads, algorithms or tracking

Hacker News

Micro – apps without ads, algorithms or tracking

For over 10 years I've been trying to accomplish something that took Claude Code and a lot of failure to realise. We need alternatives to big tech and we're not working hard enough to make that happen. In an era of addiction, usury and exploitation it's now time we seriously consider alternatives. Proton and the like worked on privacy focused individual services at a pain stakingly slow pace. Maybe for good reason. But it was also in an era pre AI. 10 years ago I was convinced the super app model would work. And that a platform needed to exist to facilitate that. Today I realised the tech doesn't matter, the idea and execution from the top down does. I put aside my technical perfectionism to try pull together a solution to some of the problems that plagued my own life with tech addiction and I rewrote and threw away this thing multiple times over the years pre AI and after. I burned VC funding, I burned bridges, I burned community trust in an open source project. But it was all in the pursuit of something I was compelled needed to exist. I use this on a daily basis probably 10+ times a day. Every person has different use cases but for me what's key is to try pull all the digital daily habits in one place and then be able to build on that. I can't replace my own google usage for mail yet but I also saw a need for something in between by private email and a work email. There's so much more I could say but essentially Micro and the app Mu ( https://mu.xyz ) is the culmination of many years of work. And it's also open source. https://github.com/micro/mu . Please provide feedback. Please tear it apart. Please poke holes in my theory. I'm not looking for hype. I really do just think we need an alternative to big tech.

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Actual performance

6points
4comments
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, model, google · Missing: mac, agents, macos
85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, open source, ide · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: apps, google, way · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
20%20% 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
15%15% 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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