Fi

Find that next best fit for your career

Hacker News

Find that next best fit for your career

Hi HN, Hope this message finds you well. I’m reaching out because I believed many of you - developer, or not may have been through similar experiences. Simply put, working through recruiters, job boards, and other such sites has been a pretty horrible experience for me. Our view is that there should be a more personalized and transparent process in applying for jobs and discovering meaningful career paths. With that being said my partner and I are in the early stages of a project and are looking for input from other people, and more specifically job seekers who may have faced the same challenges. If you have faced similar challenges, we would love to speak with you. We've started with a simple concept and put up a landing page with the hope of getting some interesting people to work with. If you're interested, would love to get your thoughts/feedback! Here is the page we've put up -- http://ww.careercinch.com/ Thank you in advance for your time.

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
69%69% 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 · Missing: mac, agents, macos
51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
50%50% 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 · Missing: plus, platform, intuitive
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% 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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