Free mentorship from experienced Product Manager and 2x startup founder

Hacker News

When I was starting out it was hard to figure out what was the best direction to go in tech. There are so many specialisations and niches and getting in contact with people is hard. We built Casa (trycasa.app) as a place to get in contact with those that seem unreachable. My colleague Dhruv (trycasa.app/dhruv) who has 10+ years in PM in the valley is using the platform to give free group sessions to anyone that requests time. Join the free group session on "Breaking into Product Management" here: https://trycasa.app/e/gXxLdYR68ZsSYNMg0yTj Join a group session with him if you're new to tech and want advice on where to start, how to start, or just want an outside perspective on your current path!

Visit product View on Hacker NewsSep 10, 2021

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

41%41% 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 · Missing: mobile apps, ios, personal

37%37% 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

31%31% 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, using · Missing: mac, agents, macos

30%30% 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

19%19% 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

16%16% 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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