OneTaskAtATime – a focused todo list app made with Claude Code

Hacker News

I'm pleased to announce the 1.0.0 beta release of OneTaskAtATime, a Windows desktop task management application built on a simple philosophy: stop managing lists, start executing tasks. Many productivity apps overwhelm users with poor prioritization, complex hierarchies, and feature bloat. OneTaskAtATime takes a different approach. The core feature is Focus Mode, which presents you with exactly one task at a time—the most important thing you should be working on right now. No distractions, no decision fatigue, just focused execution. Claude Code was instrumental in developing this application and testing it rigorously. That said, I'm looking for a few testers to try out this app and provide feedback. Let me know if you would be interested! GitHub Page: https://github.com/cmdavis25/OneTaskAtATime Beta Release : https://github.com/cmdavis25/OneTaskAtATime/releases/tag/v1....

Visit product View on Hacker NewsJan 27, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, apps, user · Missing: mac, agents, macos

82%82% 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

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: apps, users · Missing: mobile apps, ios, personal

40%40% 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

31%31% 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 · Strong signals: users · Missing: plus, platform, intuitive

24%24% 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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