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Kikker – AI-Powered Tool to Help You Land Your Dream Tech Job

Hacker News

Kikker – AI-Powered Tool to Help You Land Your Dream Tech Job

Hi HN! I’ve been working on Kikker, an AI-powered tool that helps software engineers land their dream tech jobs faster. We’ve just launched the alpha version, and I’d love for you to try it out and give me feedback. Here’s what Kikker can do: AI-Powered Resume Review: It analyzes your resume and provides personalized, actionable feedback to make it stand out to recruiters. AI-Powered Social Bios Generator: It generates tailored bios for your LinkedIn, GitHub, and other profiles that will grab the attention of hiring managers. There’s no sign-up required to try it out – just head to getkikker.com and give it a go. Right now, we’re offering free access to apply for up to 5 jobs through the platform. I’m still working on improving Kikker, so any feedback you have would be super helpful. If you have any questions, feel free to ask in the comments! Thanks, and looking forward to hearing what you think!

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Actual performance

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Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
81%81% 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.
TrustMRRLess likely to generate early MRR · Strong signals: ios, personal · Missing: mobile apps, entrepreneurs, apps
40%40% predicted probability of success on TrustMRR, 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
36%36% 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 · Missing: mac, agents, macos
31%31% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
30%30% 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
10%10% 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.

Correct prediction on native model

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