I was featured in Forbes Last Week I built RemotelyGood.us

Hacker News

Hey everyone! I'm happy to announce that we’re beginning a relaunch of the Remotely Good job board that’ll be ready in a few weeks. But as of today, find us at RemotelyGood.us! To celebrate this milestone, and our recent feature in Forbes Magazine, we are doing a giveaway. 1) Vote for us on Product Hunt https://lnkd.in/ejV-mVZf or 2) Follow us on our social media pages and comment, repost us, or tag @Remotely_good. Here’s our Forbes post on X: https://lnkd.in/eXK-hDvz Get 30 days of premium access— including AI career tools and daily job alerts, and more. Please spread the word, this ends July 31st at 11:59 PST! Thanks so much!

Visit product View on Hacker NewsJul 30, 2025

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Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

72%72% 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 NewsMay not resonate with HN audience · Strong signals: including · Missing: https docs, excited, just released

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

29%29% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

26%26% 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

23%23% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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