OO – Automated O&O Shut-Up for Windows

Hacker News

Why use Windows? Well, some people do. Why let Microsoft spy on your content? Why indeed? So, O&O Shut-Up ( https://www.oo-software.com/en/shutup10 ) claims to cut the connection and telemetry between you and Microsoft. However, when Microsoft updates your computer, the settings are reset, and you have to run O&O ShutUp again. Why not run OO which installs PowerShell 7+ if not installed, O&O Shutup, then it makes a scheduled tasks that runs the default settings after every Microsoft update? Why futz around with re-running anything? Just run OO once, and forget it. Please file any bugs if you find them. This isn't really going anywhere except to help internet users and my clients. Hope it's helpful PS - All of it generated with VS Code, Augmentcode AI ( https://www.augmentcode.com/ ), OpenSpec ( https://github.com/Fission-AI/OpenSpec ), and beads ( https://github.com/gastownhall/beads ).

Visit product View on Hacker NewsApr 26, 2026

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

67%67% 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 NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

50%50% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users · 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 · Strong signals: users · Missing: plus, platform, intuitive

28%28% 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

18%18% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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