AI Overview Hider for Google

Hacker News

I'm not going to lie to you, HN, this is just a stylesheet distributed as a browser extension because it's the easiest way for me both use it and keep it updated on all my browsers and devices. But if you want to hide AI Overviews on desktop and mobile and have someone keeping an eye out for new variants (which is the perfect word for Google finding new ways to infect their search results with them) and hiding them in a timely manner, I'm your man. Google seem to be continually adding new variants - in the last 12 hours I've pushed releases to hide AI Overviews now appearing as sections in the middle of search results, and as "People also ask" questions. If you'd rather just grab the CSS, you can get it from the GitHub repo linked to from the website.

Visit product View on Hacker NewsApr 25, 2025

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

88%88% 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.

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

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

51%51% 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

41%41% 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

16%16% 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.

Incorrect prediction on native model

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