Jo

Job Log – Job Application Tracker

Hacker News

Job Log – Job Application Tracker

Happy Friday HN! Long time lurker, first time poster here. I, along with many others in recent times, have been affected by the layoffs impacting the tech industry, and I'm currently on the software engineering job hunt. I had been tracking my job applications via Excel to help facilitate my WA state unemployment claims, but am (personally) anti-Excel / against using spreadsheets. I also wanted to explore the latest and greatest NextJS / Vercel features, so thought this would be a great time to learn something new! Job Log was never really meant to see the light of day for other users, but I thought "why not?" if it might help others in their job search hunt. Note: this was built in about a week, so will definitely be a little rough around the edges. Please be patient as I continue to build on this! You can learn more here: https://joblog-phi.vercel.app/about Feel free to leave any feedback here in this thread or email me at joblogservice@gmail.com! Hope everyone has a great weekend!

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Actual performance

3points
9comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
74%74% 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: 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.
Product HuntUnlikely to reach the leaderboard · Strong signals: user, new, email · Missing: mac, agents, macos
41%41% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, users · Missing: mobile apps, ios, entrepreneurs
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
29%29% 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
11%11% 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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