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I’m launching a new side project every day

Hacker News

Hey HN, for the past few months I’ve been launching a project almost every day. It’s a sort of experiment to see if we can build something agency-increasing every day, and we’ve learned a lot since we’ve started. You may have seen some of our more random projects of ours on HN, like: scrollwheel.js, ghostlystock, oldestsearch.com, iPod Social and we’ll have plenty more on the way soon. One fun result of starting Same Day Skunkworks is that it made the company I work at, AE Studio, start completing amazing hackathon projects (with our 150+ employees) a few times already this year. Then we decide if we want to polish them enough to turn into real skunkworks companies that spin out of AE (we sold the first skunkworks company a year ago for a number of millions of dollars) or just fun little same day skunkworks projects. They all start out as small, fun little projects and sometimes become something more. I actually have a huge backlog to get through now and it’s kinda exciting to have more awesome fun projects to bring to life. We’re gonna continue experimenting with this model to build both fun side projects and actual profitable companies too, but mostly prioritize fun agency-increasing things in the short term and just see where that takes us. We’re trying to make everything as useful as possible, so any suggestions for future projects (or advice on the random crazy Same Day Skunkworks structure we’re trying to build) would be very welcome. Thanks!

Visit product View on Hacker NewsNov 17, 2022

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

92%92% 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.

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

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: month, way, profitable · Missing: mobile apps, ios, personal

50%50% 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

46%46% 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: host, soon · Missing: plus, platform, intuitive

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

24%24% 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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