I made my commercial clipboard manager open source because it's right

Hacker News

Hey HN, Clipboard managers handle sensitive data such as passwords, personal notes, API keys, etc. To trust one you need to be sure that it doesn't send your data to third parties or store it on remote servers. With closed-source apps, you have to take the developer’s word for it. As a software engineer, I don't like that. Transparency matters. So, I decided to make my commercial clipboard manager open source. Anyone can inspect the source code, verify that data stays local and never leaves the user's device. Anyone can build the app from source and use it. At the same time, the app is still commercial, as I need to cover hosting, tooling, and development costs. I know this means anyone can build the app from source and use it for free. Or even rebrand and sell it, but I think the trade-off is worth it. What do you think about this approach? Would you trust an open-source commercial app more than a closed-source one? Do you think I made a mistake? Website: https://clipbook.app Source code: https://github.com/vladimir-ikryanov/ClipBook

Visit product View on Hacker NewsFeb 21, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user, notes · Missing: mac, agents, macos

85%85% 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.

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

59%59% 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 · Missing: supports, reddit linkedin, podcasting

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

20%20% 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

15%15% 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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