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Interviews with the founders of space startups

Hacker News

Interviews with the founders of space startups

Hi everyone! I've been working on Space Bandits, a website where I interview the founders of space startups. There are 12 on the site so far. https://www.spacebandits.io With SpaceX coming onto the scene and showing how private companies can innovate in the sector (and have big vision), space is entering a boom right now. So I wanted to showcase the most exciting space startups and tell the story of how they got started. This, I hope, will inspire others. Let me know what you think and how this could be improved, as well as who you would like to see interviewed. Thanks!

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
68%68% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting
67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
56%56% 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 · Missing: mobile apps, ios, personal
45%45% 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
29%29% 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.

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