Hindsight is a free and open-source retrospective board

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These holidays I've been working on this side project. I learned a ton and I think it has some neat little features to show: - It's a React application written in TypeScript using Parcel[1]. - No back-end. Data is shared via WebRTC directly between connected browsers. I'm using Yjs[2] to help me with that. - Synchronized timer and YouTube player (audio only). - It isn't responsive yet and lacks some polishing but I did put several hours on tweaking the UI. Things like volume slider being logarithmic instead of linear, high precision timer display using request animation frame (so no longer/shorter seconds) and force/sensitivity aware volume scrolling with both mouse wheel and trackpad, among others. I started using it in my current job and my team is super happy with the experience. Still have some work left to do though: - Actions and comments. - Different user roles, so only select people can control the timer, music, etc. - Data export. Feel free to leave feedback here or on GitHub[3]. Perhaps it could be helpful to you as well. Cheers! 1. https://parceljs.org/ 2. https://docs.yjs.dev/ 3. https://github.com/haggen/hindsight

Visit product View on Hacker NewsJan 8, 2023

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

89%89% 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

88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

60%60% 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

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: audio · 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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