Creative Chronicles (Wikipedia+ for Startups?)

Hacker News

Hi everyone, I've been building this... I don't know what it is yet.. I don't even know if it's useful to anyone, but for me, as a SV outsider, interviews and presentations from founders and builders are the closet thing I have learning more about startups. Often, the interviews before companies get 'big' are less corporate and more authentic, and I've found watching a few from founders chronologically throughout their evolution can be quite informative of how they thought about different aspects of running startups at different lifecycle stages. What is it? It's some mix of Youtube+Wikipedia+ZoomInfo. It's a week old and in a very rough state, but I'd love some feedback if anyone gets a chance to check it out. Thanks and have a nice day. Demo video: https://www.loom.com/share/fca5300bc48f46ce9e767562b4b3d4f7 Try app: https://creativechronicles.org

Visit product View on Hacker NewsAug 17, 2023

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1points

Did not reach leaderboard

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

85%85% 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: ide, io · Missing: https docs, excited, just released

72%72% 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 HuntOn track for Day 1 leaderboard · Strong signals: presentations · Missing: mac, agents, macos

62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

20%20% 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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