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To To-Do – Collaborative Task Lists with AI and Dexie.js

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To To-Do – Collaborative Task Lists with AI and Dexie.js

Hi HN, I couldn’t find a to-do app that worked the way I needed – cross-platform, offline-first, real-time collaboration – so I built one. Key features: - iOS, Android and Web with seamless sync (Dexie.js + Dexie Cloud). - Real-time collaborative lists (great for families and teams). - AI assistant for generating tasks, recipes, or workout plans. - Rich text editor with attachments and notes. I’ve been working on this for ~2 years (~2,500 hours of dev). My small team and family use it daily, and now I’d love HN’s feedback. App link: https://totodo.app/go More details in the comments – happy to answer any technical/product questions.

Visit productView on Hacker NewsAug 27, 2025
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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: tasks, notes · 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 · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: ios, way · Missing: mobile apps, personal, entrepreneurs
60%60% 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
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
20%20% 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.

Incorrect prediction on native model

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