your own personal satellite?

Hacker News

Here's a bizarre and probably a stupid question. But perhaps a fun thought experiment. If you had access to a small satellite, what would you do with it? We've managed to drop the price-point and expertise overhead required for having/operating a 5kg-class satellite to a point where a "somewhat wealthy software engineer with a laptop" could have one (i.e. $250k all in, including launch). This is not the market we're targeting by any means, but I've just realised the Venn diagram has crept in that direction. And I thought it might be worth thinking about … if just for fun. Anything beyond hobbyist astronomy/photography, kudos, etc? Example satellite: https://orbastro.com/satellites/orb-3/

Visit product View on Hacker NewsJan 20, 2021

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Hacker NewsStrong engagement from HN community · Strong signals: io, including · Missing: https docs, excited, just released

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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