FSSG – A Distraction-Free Writing Space with Focus Tracking

Hacker News

FSSG is a distraction-free web application I built to help students and professionals maintain focus during study/work sessions while taking notes. It combines focus tracking with note-taking in a clean, minimalist interface. Source: https://github.com/herniqeu/FSSG.git Key features: Distraction-free environment for deep work sessions Integrated note-taking system that persists locally Smooth animations and 3D visualizations for a modern experience You can either: Use the live version directly in your browser: https://future-seems-so-good.com/ Clone and run locally: git clone https://github.com/herniqeu/FSSG.git The project is open-source and welcomes contributions. Built this because I needed a simple, focused environment for my own study sessions without the bloat of existing solutions. Would love to hear your thoughts and feedback from the HN community!

Visit product View on Hacker NewsFeb 19, 2025

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2points

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

67%67% 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

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

57%57% 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 · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive

38%38% 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.

Incorrect prediction on native model

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