Focus Firewall – a realistic distraction blocker for Mac

Hacker News

Hey folks, I started building this app (for Mac) out of necessity to avoid distractions (like twitter, yt, hn) during working hours, especially now that I'm WFH/remote/solo and lacking the structure of a corp job schedule. I was having a hard time because a yt video or a twitter link visit would almost always becomes 2 videos or 5 mins of scrolling. There are a bunch of smart people working against you and trying to keep you in. Apart from the time we waste, we also spend our focus/attention battery charge. We get bombarded with info/content and we can only process so much every day. This aspect is more qualitative and a little harder to measure, but I think it also does have a significant impact on how our days go. Just like food, we also need to care for our "online diet". Before working on it, I tried other apps for a few months and none really stuck. They were either too analytical ("look how bad your browsing habits are") or too strict ("block everything password that only your S.O. knows"). I also didn't like solutions that needed browser extensions everywhere, nor solutions that uploaded your browsing history to some cloud (gross). Ultimately what worked was just editing /etc/hosts and pointing twitter.com to localhost. Of course I can just open the file and unblock things, but just that added friction was enough to think about it twice "damn it, gotta edit the file...". This often made me give up getting my twitter/yt fix. I ended up creating a dumb switch in the menu bar that you can "turn distractions off" = starts blocking distracting things. It looks like the internet is down just for that website. I also made it autostart everyday 9to5 so that I don't have to think about it. And of course, it's not strict at all. You can turn it off anytime and you can take breaks. Also if you're curious, our early beta users seem to continue using the app even though you can turn it off anytime – they end up using pauses, which helps manage how much time they wanna spend. Wanted to share it with y'all and would love to hear your thoughts/feedback/comments!

Visit product View on Hacker NewsJun 19, 2024

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

96%96% 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: mac, apps, user · Missing: agents, macos, agent

88%88% predicted probability of success on Product Hunt, 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

49%49% 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 · Strong signals: apps, video, month · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% 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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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