Sq

Sqrte Tasks – A Task Management App – Local-First and Privacy Minded

Hacker News

Sqrte Tasks – A Task Management App – Local-First and Privacy Minded

I have surveyed many personal task management applications but have always been left wanting. Of the ones I have tried, I appreciated the dashboard view style of Google Keep the most, but I'm not a fan of big tech owning my data and using me as a product. So, I set out to create something I could appreciate using. It solves my own problems so I'll appreciate wherever it lands, but hopefully it will solve others' problems too. This has been a pet project I've chipped away at here and there for quite a while. I believe I started even before Local First software was a thing. However, it turns out that if you're passionate about privacy and performance, you end up self-discovering many of the Local First principles. I found out later that Local First was a thing and that what I had been doing lined up with it's principles very nicely. See "Related Reading" below for more info on what Local First is if you're not familiar. The Sqrte Tasks front end can operate independent of a backend when running on a single device. Your data is stored locally in the browser and can be exported at will. I decided to open source the parts required to run standalone like this. The "premium" parts required for syncing across multiple devices (with e2e encryption) remain closed at this point but many of these parts reside in the public repo (under a different license) so that people can still see how it all works. Check out the brochure page for more info: https://tasks.sqrte.com/info Launch Sqrte Tasks Here (no account required): https://tasks.sqrte.com If you have ideas, feel free to reach out on Github: https://github.com/SqrteSoftware/tasks I hope you like this take on what todo lists can be. I would love to hear any feedback you may have. Have fun! --------- Related Reading: Local-first software: you own your data, in spite of the cloud https://news.ycombinator.com/item?id=21581444 https://www.inkandswitch.com/local-first/

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, new, single · Missing: mac, agents, macos
70%70% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting
70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
58%58% 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: personal, google, way · Missing: mobile apps, ios, entrepreneurs
36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
28%28% 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
11%11% 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.

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