Underthreaded – The Brand for Engineers

Hacker News

We've noticed a lack of quality engineering clothing. Sure, there's the standard t-shirt with code snippets and references, but that's not our style. So we created Underthreaded: a brand specifically for engineers. We make clean clothing that you can wear anywhere - if you're like us and there's no distinction between work and normal clothing. We've always loved FOSS and quality, free learning resources. They've been essential to our careers. To give back, we will be donating a portion of our profits to open source projects (see our initial choices and reasoning here https://underthreaded.com/blogs/tech/how-we-support-open-sou... .) Also, we have also starting a curated list of blogs to check out that you find here https://github.com/underthreaded/blog_list . Let us know what you think!

Visit product View on Hacker NewsAug 27, 2024

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

61%61% 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: code, open · Missing: mac, agents, macos

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

35%35% 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

25%25% 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 · Missing: arr, mrr, revenue

11%11% 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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