Instant body doubling for your ADHD (interview work trial project)

Hacker News

Hey HN community! As part of a paid work trial at our startup Flow Club (YC S21), our candidate scoped, built and marketed a simple webapp designed to boost productivity and help people, especially those with ADHD, stay focused through the power of body doubling. I'd love to show it to you! Body doubling is a popular self-management technique where doing your work in the presence of others can help you stay focused, present, and accountable while reducing the feeling of fatigue and isolation that make us prone to distraction and overthinking. We’d love to show it to you. Key features: - Quiet shared space for body doubling: Work alongside others in a (no-audio) video call. Optional Lo-fi or synthwave music if that helps. - Pomodoro timer: The timer is (very slightly) shared with other users, introducing some structure and social accountability to help you make progress. - Social to-do list: Declaring your tasks more publicly helps increase the odds of you getting them done. - Peer recognition: Work is hard, so we’ve created more incremental opportunities to give yourself and others kudos to help propel each other forward. Why did we build the Flow Club Lounge? At Flow Club, we host 1,000 live, facilitated coworking sessions every week. By harnessing the power of social accountability and motivation, we help anyone working from home, working independently, or working with ADHD get more done while feeling connected. The magic lies in the body doubling, so the Flow Club Lounge is our way to help introduce body doubling to everyone more easily. Thank you for your support, and happy focusing! Give it a try (no signup required unless you want to turn your camera on!): https://in.flow.club/lounge/ Give it a try and share your feedback. Happy focusing!

Visit product View on Hacker NewsMay 21, 2023

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91%91% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: video, users, way · Missing: mobile apps, ios, personal

59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: adhd, ide, 000 · Missing: https docs, excited, just released

55%55% 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: host, users · Missing: plus, platform, intuitive

47%47% 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

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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