ScrollPods – Scroll hands-free on your Mac with AirPods

Hacker News

I’ve been trying to read PDFs and articles while rocking my baby boy to sleep in front of our iMac. Not the easiest combination, and yes, you could argue I shouldn’t multitask, but you know how it is. I couldn’t help myself and ended up building an app to make it easier. It’s called ScrollPods. You tilt your head gently up or down while wearing AirPods, and your Mac scrolls intuitively. It works in web browsers, PDFs, documents, social media, spreadsheets, basically anywhere you normally scroll up and down. I am still surprised at how intuitive it feels. Key Points: - App size is 3 MB - Uses minimal CPU (<5 percent) and battery when active - Low RAM usage (around 50–70 MB) - Works offline, fully on device - System-wide scrolling in any app - Supports AirPods 3rd gen+, AirPods Pro, AirPods Max and Beats Fit Pro† - Settings page for fine-tuning to your personal needs - Supports English, French and German - Automatic 7 day free trial with no sign-up, no login, no email - If you like it you buy it for $ 4.99 * When running in the background with just the menu bar icon, this was for a M1 iMac. † I think more Beats models might work, but Apple doesn’t publish a full compatibility list. If you’re unsure, just try it out during the 7 day trial. The app will tell you right away if your headphones are unsupported.

Visit product View on Hacker NewsNov 21, 2025

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

96%96% 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: mac, model, apple · Missing: agents, macos, agent

92%92% predicted probability of success on Product Hunt, 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.

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

49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

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

21%21% 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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