I Got Fired from my FinTech Job so I built this

Hacker News

I'm Cliff, – nice to meet you. Layoffrecruit is something that I wish existed for me less than 2 years ago. You see, I was dealt a devastating blow when I got laid off from my fintech job after 6 years. I felt hurt, lost, and like a complete failure. I had no idea what my next move would be. Today, thousands of tech talent are being laid off by tech companies every day, 138,302 in 2023 alone. And, just as I felt, I'm sure those affected by these current layoffs feel the same way today – lost and devastated. This is why I built Layoffrecruit – to help recently laid-off tech talent find new jobs and get back on their feet. LayoffRecruit is the world's first job board for any employee affected by layoffs. We help connect talent with startups and top tech companies looking to hire them. I'm stoked to be sharing this with the community. I'd love to know what you think here, or you can hit us up at hello (at) layoffrecruit.com if you have questions/feedback/suggestions!

Visit product View on Hacker NewsMar 15, 2023

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · 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.

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

55%55% 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: new · Missing: mac, agents, macos

47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

39%39% 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

33%33% 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

17%17% 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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