I quit my job and made an automatic time tracker

Hacker News

Hey Hacker News! This is my first post here. About 5 months ago, I left my job because I was completely burnt out. After taking some time off, I started freelancing. But I found tracking my time to be a real hassle as I kept forgetting to start or stop the timer and often had no idea what I’d worked on. So, I decided to build Taim as a side project, while also working now on some freelancing gigs. Taim is going to be automated time tracking tool for freelancers and teams. It’s designed to make tracking time effortless and accurate, so you can focus on your work and not worry about the clock. I’m excited to share this with you all and would love your feedback! Currently planning to launch it to the public in a few months.

Visit product View on Hacker NewsJul 16, 2024

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

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.

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

66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

27%27% 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

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: time tracking · 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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