The buildinpublic companion for AI product founders

Hacker News

Hey there! I've recently launched a platform to help indie hackers along with their #buidinpublic journey. Twitter is fine for many, but if you want to have a visual tool that tracks all your milestones, collects feedback from your audience, allows you to create polls and, more importantly, allows you to get infinite roasts about your product, then I think this might be useful for you! Many self-proclaimed product experts charge hundreds of dollars for roasting your page, so I think this Roast x Roast approach could be super interesting and can help founders accelerate their path to Product Market Fit, without spending a fortune on it! There is an initial focus on AI-based products but everyone can really submit theirs (and select "other" as the category). Happy to answer any questions you may have!

Visit product View on Hacker NewsJul 7, 2023

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: visual · Missing: mac, agents, macos

78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

33%33% 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 · Strong signals: platform · Missing: plus, intuitive, reviews

23%23% 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

14%14% 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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